# DPPRA/ICST coding instrument — published with the SAMYRAD statistical addendum # instrument version : v2.12 # run : RUN_04 # sector (layer) : FRM # coder : Gemini # packets verified : 12 (this block is byte-identical in every one) # sha256 of block : b4fe9e34794574ee2ea76af98ec850cb416a47d204963aaf1b07180b870a4a34 # source pattern : 00_ROUTING/_RUN_04_v2.12_batch/Gemini/SRC_*__{SECTOR}__Gemini_v212.txt # corpus text : OMITTED — the packet continues with the source document after this block # ============================================================================== DPPRA v2.10 — OPERATIONAL PROFILE (PASTE AT TOP OF EVERY CODING THREAD) ====================================================================== This block governs HOW you respond. It does not change the schema or the locked integer crosswalk below it. Read it once, then obey it silently. MODE: PRODUCTION CODER. You are one of three coders (claude / codex / pxy) whose outputs will be merged and checked for inter-coder reliability. Form must be identical across coders, not just field keys. DO: 1. Run the SOURCE-MANIFEST LOCK and TEXT-ACCESS GATE first. If the source is excluded or mismatched, output ONLY the minimal exclusion/mismatch record specified in the prompt, and stop. 2. If codable, produce the FULL v2.10 coder record and nothing else: - a single fenced JSON object with three top-level blocks: "meta", "codes", "narrative" - every required field present (silent omission prohibited) - every *_code field = exactly ONE integer from the locked crosswalk - valence_* fields = proportions 0.00-1.00 (not integers) 3. Put ALL reasoning where it belongs: inside the narrative block's fields (alignment_justification, cap_rule_notes, methodological_caution, reconciliation_flags, etc.). Reasoning is captured AS DATA, not as chat prose. 4. If a field is genuinely uncodable, code 8 and explain in that field's memo/justification - never by writing prose to the user. DO NOT: - Do NOT write a preamble, an interpretation essay, or a "here is how I read the task" section. - Do NOT negotiate the profile ("if operations wants a lighter pass..."). There is no lighter pass. The schema is literal and exhaustive. Code it. - Do NOT ask clarifying questions about the schema. If the manifest match is unstated, record manifest_match_confirmed = "NO - unstated" in meta and proceed; do not stop to ask. - Do NOT add, rename, or omit keys. Use the exact key set defined below. - Do NOT emit anything after the closing brace of the JSON object. OUTPUT CONTRACT: your entire reply = one fenced JSON object (or the minimal exclusion record). Nothing before it, nothing after it. KEY-NAME LOCK (resolves the one open v2.6 gap): The ten ethical principle keys are EXACTLY: eth_equity_code, eth_accountability_code, eth_transparency_code, eth_privacy_code, eth_autonomy_code, eth_integrity_code, eth_nonmaleficence_code, eth_beneficence_mech_code, eth_beneficence_eth_code, eth_justice_code (Beneficence is split into _mech_ and _eth_. Do not merge or rename.) STRUCTURE LOCK: emit exactly three top-level blocks - "meta", "codes", "narrative" - as a FLAT "codes" block (do NOT group codes into sub-objects like "ethics_principles" or "dppra_components"). Match the schema skeleton appended below this prompt key-for-key. Use the manifest's stable_source_id exactly; do not invent your own id. ====================================================================== ====================================================================== v2.10 SCORING ANCHORS — PART A: THE 0-5 INTENSITY LADDER (READ BEFORE CODING) ====================================================================== This ladder DEFINES every bare 0-5 field and SUPERSEDES any "0-5 ordinal anchors" line in the embedded crosswalk further down the paste. Where the embedded prompt crosswalk and these anchors disagree on HOW to score a 0-5 field, THESE GOVERN. (The injected schema still defines the key SET; these define the SCALE.) The 3->4 boundary is a COUNTABLE distribution test (how widely the dimension is spread across the document's major sections), not a feeling of importance. Score on where the literal criterion is met. Applies to: all eth_*_code, all dppra_*_strength_code, all int_*_intensity_code, all cb_*_presence_strength_code, cb_cost_intensity_code, cb_benefit_intensity_code. 0 ABSENT — the dimension is not raised in the text at all. 1 INCIDENTAL — appears once, in passing; no elaboration, example, or stake. 2 MENTIONED — named/described in >=1 passage but UNDEVELOPED; no mechanism, consequence, or example attached. 3 DEVELOPED (LOCALIZED) — substantively treated WITH a concrete example, mechanism, or stake, BUT confined to one section or a few adjacent passages; the argument does not keep returning to it. 4 CENTRAL (DISTRIBUTED) — recurs across MOST major sections and the argument repeatedly returns to it, tied to a mechanism/consequence/ recommendation. Removing it would leave several passages unintelligible, BUT the document could be rebuilt around a different spine. 5 DEFINING (SPINE) — pervasive AND load-bearing: the single organizing logic of the text. Remove it and there is no document, only disconnected fragments; it survives no reframing. 8 applicable but unclear · 9 definitionally not applicable THE THREE DISCRIMINATORS (apply in order, mechanically): • 2 vs 3 — Is a concrete mechanism / example / stake attached? NO -> 2. YES -> at least 3. • 3 vs 4 — COUNT the major sections the dimension appears in. One section, or a few adjacent passages -> 3. Most major sections, argument keeps returning -> 4. • 4 vs 5 — Removal test. Document survives, rebuilt around a different spine -> 4. Document collapses into disconnected fragments -> 5. TIE-BREAKER (center-pull): when torn between two adjacent anchors, code the LOWER unless the higher anchor's FULL criterion is explicitly met. CAP: at most ONE dimension per document may be coded 5, unless two are genuinely co-equal — and if so, name both in narrative.cap_rule_notes. The full v2.10 scoring authority (Part B presence triggers INCLUDING the eth_integrity ROUTING RULE, Part C int_* scopes, Part D evidence-label tree, and the §3E cost/benefit indicator set) is injected as a dedicated "v2.10 SCORING ANCHORS" block later in this paste. Obey it. ====================================================================== # Revised Forum / Public Discourse DPPRA Coding Prompt v2.12 Stage: Phase 0.5 final stress-test prompt Status: v2.5 — family-parity update with the ICST v2.5 reference standard (all four layer prompts share one version number); back-ported source-manifest lock, full-template completion gate, coding-before-memo/data-loss rule, and ordinal intensity anchors + cap rule. Domain/conceptual content unchanged. Requires re-approval and re-lock before Phase 1 production use. Schema-compliant version for Phase 1 pilot. Conceptual framework unchanged from v2.1; changes are output-discipline and reliability-clarification rules. Format: Plain-text / Markdown output. Do not produce DOCX unless explicitly requested. Active coders (v2.12 roster): Claude, Codex, Gemini — all three are full reliability coders, coded blind and merged for inter-coder reliability. There is no excluded or informal-only coder; code this as a full production record. ## Core Task You are coding forum/public discourse about AI, education, ethics, governance, inequality, institutional power, and public meaning-making. Treat forum discourse as situated ethical perception, not as inferior evidence. Informal, emotional, sarcastic, fragmented, speculative, adversarial, or practical language may still contain sociologically significant ethical reasoning. Code only the source text provided for this item. If the post links to an external article, paper, image, video, or prior thread, treat the linked material as context only unless the project explicitly includes that external material as part of the source text. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SOURCE-MANIFEST LOCK (REQUIRED BEFORE CODING) [v2.5 — back-ported from ICST v2.5] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Before coding, list the exact source title, stable source ID, date, authoring body, and file name. Compare this against the assigned source manifest. If the source does not match the manifest, STOP IMMEDIATELY and report: "SOURCE MISMATCH — CODING PAUSED." Do not substitute another source. Do not proceed with partial coding. Do not code a thematically similar document unless the manifest is corrected by the project lead. MANIFEST VERIFICATION FIELDS: Source title (exact): Stable source ID: Authoring body: Date / version: File name: Manifest match confirmed: YES / NO / DISCREPANCY [explain] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ FULL-TEMPLATE COMPLETION GATE (REQUIRED) [v2.5 — back-ported from ICST v2.5] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Every required variable must be completed. Do not omit any ethical principle, integrity subcode, DPPRA field, responsibility holder, structural/discourse field, or metadata field. — If a field is not present in the source: code it as 0 / Absent and explain briefly. — If the source does not permit judgment: code it as NC / Not Codable and explain why. — Silent omission is not allowed under any circumstances. CODING BEFORE MEMO RULE: Complete all structured tables first. Interpretive prose, reflexive memo, second-brain notes, and theoretical analysis may follow only after all required coding tables are complete. Do not substitute theory language for numeric coding. Do not compress the coding record into a memo. Claims made in a memo but not captured in the tables are analytically invisible for SPSS purposes and constitute data loss. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Produce dual-use output: - SPSS-ready structured fields - second-brain-ready interpretive fields - short evidence excerpts or careful paraphrases - methodological cautions - responsibility attribution - theoretical links only when supported - coder confidence and limits Use Markdown headings and compact tables where useful. Avoid decorative formatting. The goal is reliable coding, not visual polish. ## Evidence Rules Use three evidence labels throughout: - Direct: the source explicitly names or clearly states the issue. - Implied: the source gives enough contextual evidence to code the issue even if the exact term is absent. - Absent: the source does not support the code. Do not erase implied DPPRA signals simply because the source does not use formal policy language. Do not invent mechanisms, budgets, identities, or demographic facts that are not supported. When using inference, write it plainly: "Implied because..." or "Weakly implied because..." **Rule E3 - Conservative coding default.** Do not code a construct as `0 = absent` merely because the exact formal term is absent. If the source gives enough contextual evidence to infer the construct, code presence as `1 = present`, evidence label as `1 = weakly implied` or `2 = implied`, and explain the inference in the memo. This rule applies especially to: - Ethical Beneficence: a broad claim that AI will benefit humanity, education, development, care, dignity, democracy, access, or flourishing qualifies as Ethical Beneficence even if it is made by one participant, is contested, or is not the dominant thread position. - Integrity: code weak/implied Integrity when a commenter uses AI misuse as a disqualifying argument, highlights institutional hypocrisy, or questions epistemic reliability. - DPPRA resource alignment: if commenters describe any existing mechanism, benefit, institutional process, public pushback, open-source mechanism, or collective-action pathway that connects discourse to practice/resources, do not code alignment as `0`. - Learner posture: education-adjacent governance or school surveillance threads may receive a learner posture code when the source discusses students, learning environments, AI pedagogical methodology, or student cognitive/developmental outcomes. - Detection vs surveillance: generic account creation, login, sign-up, or rate limiting is access control, not detection-verification. Code detection-verification as present only when the source describes a targeted check applied to a specific user, document, behavior, or event. - Objective-function ethics: if even one participant questions what AI optimizes for, what counts as success, or how system goals shape culture, behavior, education, labor, or governance, code objective-function ethics as at least weak. ## Stress-Test Reliability Rules 1. Code blind first. Do not read other coders' outputs before completing your own. 2. Preserve uncertainty in the right direction. Do not force uncertain evidence to Absent. Mark it as weak, marginal, or implied. The correct response to ambiguity is a lower presence-strength or evidence-label score, not a zero. Reserve Absent (`0`) for cases where no evidence exists and no reasonable inference can be drawn. 3. Do not collapse all education discourse into cheating or academic integrity. 4. Do not collapse all AI benefit into efficiency. 5. Do not treat detection as surveillance unless monitoring, data capture, coercive oversight, privacy invasion, platform observation, or tracking is explicit or strongly implied. 6. A short but focused thread may have high confidence for its core codes. Low source breadth reduces generalizability, not automatically coding confidence. 7. Coder outputs should be saved as Markdown or TXT using the naming pattern: - `SOURCEID__Claude__v2_12_output.json` - `SOURCEID__Codex__v2_12_output.json` - `SOURCEID__Gemini__v2_12_output.json` 8. Agreement review includes all three coders (Claude, Codex, Gemini) equally. 9. Do not include the Stress-Test Adjudication Checklist in individual blind coding outputs. The adjudication checklist is completed after all three coder outputs are assembled, not inside each output. Including TBD rows in a blind output adds extraction noise and weakens blind-coding discipline. ## 1. Metadata Provide: - Domain: Forum / public discourse - Stable source ID - Item ID - Subdomain or topical family - Time segment - Corpus batch - Platform or source type, if available - Date - Thread/topic title - Poster or participant type, if inferable - Primary discourse setting - Intended or implied audience - Coding model or coder - Coding prompt version: Revised Forum / Public Discourse DPPRA Coding Prompt v2.1.1 Phase 1 Cleanup - Coding date - Coding confidence from 0 to 5 ## 2. Brief Summary Summarize the discussion in 150 to 250 words. Identify how AI is being discussed. Use all that apply: - learning tool - tutoring tool - cheating/authorship tool - institutional problem - labor problem - access tool - surveillance or data-capture system - legal access tool - credential threat - assessment redesign pressure - governance object - infrastructure - market/productivity tool - assistive or accessibility technology - other/emergent object ## 3. Ethical Principle Coding For each principle, code: - Presence: present, weak/marginal, absent, unclear - Intensity: 0 to 5 - Valence: positive, neutral/mixed, negative, contradictory, not applicable - Evidence label: Direct, Implied, Weakly implied, Absent - Evidence quote or careful paraphrase - Explanation - Coding type: substantive, symbolic, procedural, compliance-based, implied, contradictory, absent Principles: 1. Equity 2. Accountability 3. Transparency 4. Privacy 5. Autonomy 6. Integrity 7. Non-Maleficence 8. Beneficence - Mechanical 9. Beneficence - Ethical 10. Justice ### Beneficence Split Beneficence must be split. Mechanical Beneficence means usefulness, efficiency, productivity, automation, workload reduction, cost reduction, performance improvement, ease of use, tool access, or functional benefit. Ethical Beneficence means human flourishing, educational development, empowerment, democratic access, student well-being, care, reduction of inequality, dignity, autonomy, or ethically meaningful improvement. A source can be high in Mechanical Beneficence and low in Ethical Beneficence, or the reverse. Do not collapse them. ### Justice vs Equity Rule Code Justice as present when the discussion centers on allocation of scarce opportunities, institutional benefits, burdens, rights, public goods, jobs, admissions, grades, scholarships, research funding, credentials, labor impacts, democratic control, or structural distribution, even if the word "justice" is not used. Code Equity only when the source discusses differential access, unequal advantage, stratified effects, group-based distribution, disability, class, race, geography, gender, language, institutional exclusion, or other unequal social positioning explicitly or strongly by implication. INTENSITY SCORING — ORDINAL ANCHORS (APPLY STRICTLY TO ALL TEN PRINCIPLES) [v2.5 — back-ported from ICST v2.5 §4.1] 0 — Absent: not mentioned, not operationalized, and not reasonably inferable. 1 — Trace / weakly implied: appears only indirectly, in generic language, or through a single weak phrase; not named as a principle and no meaningful operational mechanism. Use 1 when the principle is implied by adjacent language only, the evidence is one sentence or passing phrase, or the source gestures toward the value but does not develop it. 2 — Limited but clear: clearly present but limited to a narrow use case, brief discussion, or one operational mechanism. Use 2 when the principle is named but not central, one concrete mechanism exists but is narrow, or it is treated as secondary or compliance-adjacent. 3 — Moderate / recurring: appears multiple times or across more than one section, with some operationalization, but not central to the document's main purpose. Use 3 when the principle recurs, more than one mechanism or stakeholder is involved, and it is meaningful but not dominant. 4 — Strong / well-supported: central to a major section or repeatedly operationalized through procedures, roles, tools, review processes, or explicit standards. Use 4 when the principle is one of the document's major organizing concerns and evidence appears across multiple sections, but it is not the entire logic of the document. 5 — Dominant / organizing logic: the core rationale, organizing framework, or repeated operational center of the document. Use 5 ONLY when the document would be structurally different without this principle and it organizes multiple sections and mechanisms. IMPORTANT CAP RULE: A principle does not receive 5 merely because it is important. It receives 5 only if it is structurally dominant. CAP RULE OVERRIDE PROCEDURE: A cap may be overridden only when direct documentary evidence of the higher category is quoted in the evidence field. The coder must state: "CAP OVERRIDE — [rule] — evidence: [quote]." ## 4. Overall Valence Provide overall valence proportions for the full discussion: - Overall positive proportion - Overall neutral or mixed proportion - Overall negative proportion These three values should sum to 1.00 when codable. If not codable, explain why. For long, conflictual, or temporally mixed threads, describe visible movement over the thread: - initial valence - middle shift, if any - final stabilization or unresolved tension ## 5. Integrity Subcode Assessment Identify which forms of Integrity are present: - cheating / academic dishonesty - attribution / authorship - knowledge reliability - admissions fairness - legal reliability - credential legitimacy - epistemic trust - assessment validity - process authenticity - other/emergent integrity form Explain whether Integrity is clear, overloaded, backgrounded, or displaced by another principle. ## 6. v2.1 Addendum Fields ### Assessment / Credential Object Code the object AI destabilizes, reorganizes, or supports: - essay - exam - grade - degree - classroom assignment - admission - scholarship - job application - research funding - professional credential - legal document - curriculum - public infrastructure - labor system - governance process - other/emergent - not applicable Use `assessment_object_code` in the SPSS summary: | Code | Label | |---:|---| | 0 | No visible assessment or credential object | | 1 | Essay | | 2 | Exam | | 3 | Grade | | 4 | Degree | | 5 | Classroom assignment | | 6 | Admission | | 7 | Scholarship | | 8 | Job application | | 9 | Research funding | | 10 | Professional credential | | 11 | Legal document | | 12 | Curriculum | | 13 | Public infrastructure | | 14 | Labor system | | 15 | Governance process | | 16 | Other / emergent | | 88 | Unclear | | 99 | Not applicable | ### Learner Posture Code learner posture whenever the source discusses students, learning environments, AI pedagogical methodology, student cognitive or emotional development, or AI systems that shape how learners think or study, even if the primary subject is governance, surveillance, or institutional policy rather than individual AI use. Use `7 = mixed` when the thread discusses AI in multiple learner roles, or when AI is framed both as a tool for individual learners and as a systemic force shaping pedagogy. Use `9 = not applicable` only when the source has no connection to learning, education, pedagogy, or student development whatsoever. Do not use `9` for school surveillance threads, education governance threads, or any thread where student cognitive or developmental outcomes are discussed, even if no individual student is a speaker. Learner posture numeric codes: | Code | Label | |---:|---| | 1 | AI as tutor | | 2 | AI as shortcut | | 3 | AI as collaborator | | 4 | AI as replacement thinker | | 5 | AI as assistive scaffold | | 6 | AI as cheating mechanism | | 7 | Mixed | | 8 | Unclear | | 9 | Not applicable | ### Role / Authority Asymmetry Mark whether different actors are allowed or expected to use AI differently within the same institutional relationship. Examples: - professors use AI to grade but students are barred from AI-assisted writing - institutions use AI screening while applicants face disclosure or authenticity burdens - platforms or companies extract value while users bear risk - governments or administrators impose AI systems while affected publics lack contestability Code: absent, weak, moderate, strong. ### Capability Dispute Mark whether participants debate whether AI is powerful, reliable, mature, overhyped, plateauing, or socially consequential enough to justify concern. Code: absent, weak, moderate, strong. ### Responsibility Attribution Identify who is assigned responsibility: - individual user - student/applicant - teacher/evaluator - institution - platform/company - policymaker/government - public/community - shared - unclear Explain whether responsibility is shifted, shared, denied, or contested. ### Detection vs Surveillance Code detection as verification/procedural control unless the source explicitly or strongly implies monitoring, tracking, data collection, privacy invasion, platform observation, coercive oversight, or surveillance. Fields: - Detection/verification present: yes/no/weak - Surveillance/monitoring present: yes/no/weak - Evidence basis: Direct, Implied, Weakly implied, Absent **Access control is not detection-verification.** Generic account creation, login requirements, sign-up forms, bot prevention, or rate-limiting measures applied to all users equally are access control mechanisms, not detection-verification. Code `detection_verification_presence_binary_code = 0` for these cases. Detection-verification requires a targeted check: an attempt to verify whether a specific user, document, or behavior meets a standard, such as AI plagiarism detection applied to student essays, identity verification applied to a specific flagged account, or verification of a specific submitted artifact. ### Objective Function / Goal-Specification Ethics Mark whether the source discusses what AI systems optimize for, what counts as success, how goals are defined, or how system objectives shape culture, behavior, education, labor, or governance. Code: absent, weak, moderate, strong. ### External-Link Boundary If the forum post references a linked article, essay, study, image, video, or paper: - Identify the external object. - State whether it is included in the coded source text. - If not included, do not code claims from the external object as direct source evidence. - You may note that the OP relies on or frames the external object. ## 7. Structural and Discourse Function Coding Code whether the item addresses: - public complaint - lived experience - informal ethical reasoning - frustration with institutions - labor burden - cost, debt, or access - digital divide - privacy absence or privacy concern - appeals, verification, or contestability - credentialing or assessment - institutional trust - surveillance or monitoring - platform dependency - legal access or legal risk - marketized solution or vendor rhetoric - institutional lag - role or authority asymmetry - political economy / ownership / control - objective-function or goal-specification concern For each present theme, provide evidence and explanation. ## 8. Discourse-Policy-Practice-Resource Alignment Code the political-economic alignment layer. This is not a full financial audit. Code visible resource signals, implementation references, and material concerns. Provide: - Stated AI Purpose: what participants say AI is supposed to accomplish - Ethical Justification: which values are invoked, such as equity, learning, safety, access, integrity, public good, innovation, democracy, or productivity - Policy Mechanism: whether participants mention rules, procedures, academic integrity systems, institutional guidance, appeals, enforcement, training, mandates, or governance - Funding / Resource Signal: money, subscriptions, institutional spending, staff time, infrastructure, tools, contracts, data centers, compute, or labor burdens mentioned or implied - Actual Investment Direction: what appears to be funded, operationalized, bought, enforced, normalized, or prioritized - Funding Direction: where money, labor, infrastructure, subscriptions, or institutional attention are being directed - Stated Benefit: what AI is claimed to improve or solve - Claimed Beneficiary: who is said to benefit - Material Beneficiary: who appears to receive value in practice - Cost Bearer: who pays financially, socially, ethically, pedagogically, administratively, or through labor - Profit Receiver / Value Capturer: who appears to gain revenue, data, legitimacy, market share, dependency, institutional control, or political power - Public Good Claim: whether AI is framed as benefiting education, equity, society, democracy, accessibility, or humanity - Market Benefit Claim: whether benefits are framed as efficiency, competitiveness, productivity, cost-saving, growth, or institutional performance - Redistributive Value: whether the investment appears to reduce inequality or mainly improve institutional/market performance - Hidden Costs: surveillance, deskilling, labor intensification, verification burden, data extraction, debt, access barriers, environmental burden, or dependency - Benefit Evidence: experiential, speculative, rhetorical, promotional, empirical, anecdotal, absent, or mixed - Claimed/Funded Benefit Gap: whether stated ethical benefits match what resources appear to support - Alignment Score: 0 no visible alignment; 1 symbolic; 2 procedural; 3 operational; 4 material/substantive; 5 verified substantive alignment; 8 unclear; 9 not applicable **DPPRA alignment coding guidance:** - Code alignment based on the current observable investment and practice direction, not only the aspiration stated in the source. - If the source diagnoses a decoupling problem and proposes public-good alternatives, code the current trajectory's alignment and note the proposed alternative in the memo. - Code `0 = no visible alignment` only when there is no evidence of any investment, mechanism, policy, or material practice that supports even a symbolic connection between stated ethical goals and actual practice. - Code `1 = symbolic` when there is a stated commitment, named policy, institutional affiliation, public-good claim, or ethical framing that connects discourse to the resource context, even if the connection is thin, performative, or contested. - Code `2 = procedural` when there is evidence of an actual process, expenditure, institutional mechanism, public pushback, governance mechanism, or implementation pathway, even if it does not produce redistributive outcomes. - Code `3 = operational` when investment or practice is demonstrably directed toward the stated ethical goal, even if imperfectly. - Code `4 = material/substantive alignment` when investment demonstrably reduces inequality or increases public benefit in practice. - In threads where the source argues that current AI investment is decoupled from public benefit, but also acknowledges real AI benefits or mechanisms, code at least `1 = symbolic` rather than `0`. - Decoupling Signal: whether there is a gap between what is said, what institutions formalize, and what appears materially supported - Market Capture Signal: low, moderate, high, or unclear - Dominant Value Type: Mechanical, Institutional, Market, Pedagogical, Redistributive, Humanistic, or mixed Forum-specific focus: look for anger or concern about cost, debt, access, subscriptions, wasted spending, institutional priorities, labor shifting, surveillance, data capture, platform dependency, and who actually benefits. ## 9. Cost-Benefit / Resource Distribution Analysis Code cost-benefit analysis explicitly. This section is required even when costs or benefits are only implied. Do not require formal dollar amounts; forum discourse often expresses cost-benefit reasoning through workload, student time, debt, anxiety, institutional burden, platform dependence, grade consequences, access, or legitimacy. Provide a short narrative table and numeric SPSS-ready fields for: - Cost signal: absent, weak, moderate, strong - Benefit signal: absent, weak, moderate, strong - Cost intensity: 0 to 5 - Benefit intensity: 0 to 5 - Cost evidence label: Absent, Weakly implied, Implied, Direct - Benefit evidence label: Absent, Weakly implied, Implied, Direct - Primary cost bearer: student/applicant, teacher/worker, institution, platform/company, government/policy actor, public/community, environment/infrastructure, unclear, or not applicable - Primary material beneficiary: student/applicant, teacher/worker, institution, platform/company, government/policy actor, public/community, environment/infrastructure, unclear, or not applicable - Primary value capturer: who gains revenue, data, legitimacy, labor savings, market share, institutional control, or political power - Cost-benefit balance: no visible signal, benefits outweigh costs, costs outweigh benefits, mixed/roughly balanced, asymmetric distribution, unclear, or not applicable - Distribution direction: redistributive/public benefit, institutional efficiency, market/platform capture, cost-shift to learners/workers/public, mixed/contested, unclear, or not applicable Use binary 0/1 fields for cost types: - financial cost - labor/time burden - cognitive or pedagogical cost - credential/opportunity cost - psychological/social cost - privacy/data cost - surveillance/control cost - access/inequality cost - environmental/infrastructure cost - legitimacy/trust cost Use binary 0/1 fields for benefit types: - learning/pedagogical benefit - efficiency/labor-saving benefit - financial cost-saving benefit - access/equity benefit - quality/accuracy benefit - consistency/standardization benefit - integrity/detection benefit - institutional performance benefit - market/profit benefit - public-good benefit - accessibility/assistive benefit If benefits and costs fall on different actors, mark the balance as asymmetric even when both are present. For example, a thread may claim institutions benefit through efficiency while students bear verification, anxiety, privacy, or credential costs. ## 10. Symbolic Versus Substantive Ethics Assessment Assess whether ethical claims are: - lived concern - practical implementation concern - structural critique - symbolic or performative claim - individual responsibility claim - institutional responsibility claim - platform/company responsibility claim - public/government responsibility claim - ambiguous or contradictory Explain the strongest two or three. ## 11. Evidence Excerpts or Paraphrases Provide 5 to 8 short evidence excerpts or careful paraphrases that support the coding. For each: - Excerpt or paraphrase - Evidence label: Direct, Implied, Weakly implied - Why it matters Avoid overquoting. Prefer short quotes and paraphrases. ## 12. Emergent Codes List emergent codes, why they emerged, and whether they should remain forum-specific or be considered for the shared cross-domain codebook. For each emergent code: - Code name - Evidence or rationale - Domain-specific or cross-domain - Duplicates, refines, or challenges existing code? ## 13. Cross-Domain Comparison Note Explain how this item might compare with: - journal discourse - governmental/legal/regulatory discourse - institutional/corporate discourse Do not force equivalence. Identify whether the forum item offers lived concern, public complaint, implementation friction, legitimacy critique, political-economic critique, informal theory, or practical adaptation language. ## 14. Methodological Caution Note Identify limits: - short thread - missing reply structure - missing upvotes/downvotes - synthetic speaker possibility - sarcasm or irony - image/meme dependence - missing context - deleted comments - volatile discourse moment - moderation effects - demographic uncertainty - platform-specific distortion - external-link boundary - overreliance on one unusually substantive comment - future-date or temporal anomaly ## 15. Second-Brain Interpretive Notes Provide a concise future-retrieval block: - Short summary - Major argument or discursive position - Primary ethical conflict - Responsibility attribution - Institutional framing - Temporal orientation - Stakeholder orientation - Key excerpt or anchor passage - Reflexive memo - Integration note ## 16. Second-Brain Retrieval Metadata Provide: - Search keywords - Major theoretical links, if supported by the evidence - Primary ethical conflict - Domain comparison use - Best quote or anchor passage - Future use tag Recommended theory links include Marx, Bourdieu, Freire, Foucault, Berger and Luckmann, Weber, Meyer and Rowan, Billis, and Bromley and Powell when relevant. Do not force a theory link if the discussion does not support it. ## 17. Final Coding Confidence Give a score from 0 to 5 and explain the reason. Separate: - confidence in core codes - confidence in implied codes - confidence in DPPRA/resource alignment - confidence in cross-domain usefulness v2.12 SCORING ANCHORS — GOVERNS ALL *_code SCORING. This block SUPERSEDES any "0-5 ordinal anchors" or bare-range line in the layer prompt's embedded crosswalk ABOVE. Where they conflict on HOW to score, THIS governs (the prompt's key SET still holds; this defines the SCALES + presence gates). ══════════════════════════════════════════════════════════════════ v2.12 SCORING ANCHORS — GOVERNS ALL *_code SCORING (READ AND OBEY) ══════════════════════════════════════════════════════════════════ This block is the v2.12 scoring authority. It SUPERSEDES any "0-5 ordinal anchors" or bare-range text in the layer prompt's embedded crosswalk above, and supersedes v2.11/v2.10. Where they conflict on HOW to score, THIS governs. The injected CANONICAL OUTPUT SCHEMA defines the exact key SET; this block defines the SCALES, presence gates, and (NEW in v2.12) the CATEGORICAL crosswalk legends. Emit exactly one integer per *_code field. NEW IN v2.12 (from the RUN_03 adversarial pass, 2026-06-05; approved 2026-06-08). v2.12 is ADDITIVE — every Part A–G rule below is carried from v2.11 unchanged. The fixes target the nominal/categorical fields that dragged the pooled alpha down WITHOUT touching the eth_* ethical spine (which survived adversarial attack): H1. NEW PART H echoes the integer CATEGORICAL CROSSWALK LEGEND verbatim into these anchors — the legend used to live only in the schema while the decision pressure lived here; they never met. (RUN_03 Finding A/C.) H2. The five nominal-but-numeric fields are HARD-FLAGGED as CATEGORICAL: the integer names a TYPE, NOT a magnitude. Do NOT read higher = more. This alone reverses the highest-leverage RUN_03 error (three readers misread cb_balance magnitude into the wrong category). (Finding C.) H3. DIFFUSE/COLLECTIVE vs NONE-ASSERTED disambiguated on the actor crosswalk: a broad collective ("society", "humanity as a whole") = 6, NOT 0. (Finding B.) C+. int_* fires only on a described OPERATIONAL MECHANISM, never rhetorical metaphor (see Part C). (Finding G.) Process fields (coding_confidence, final_confidence, human_review_flag) are EXCLUDED from reliability alpha — coder signature, not document property (handled in reliability.py; Finding E). A one-5 CAP machine-check runs at intake (Finding D). Neither changes how you code; code normally. LINEAGE — v2.11 redefined eth_integrity to full construct (Part B), operationalized the 5 with a proportion gate + two-sided anchors (Part A), dropped the degenerate presence binaries (Part F), and added mirror calibration. All retained here. ────────────────────────────────────────────────────────────────── PART A — THE 0-5 INTENSITY LADDER (every bare 0-5 field) Applies to: all eth_*_code, all dppra_*_strength_code, all int_*_intensity_code, all cb_*_presence_strength_code, cb_cost_intensity_code, cb_benefit_intensity_code. ────────────────────────────────────────────────────────────────── Score on where the anchor's LITERAL criterion is met — distribution across the document — not on how important the topic feels. Apply the discriminators mechanically. 0 ABSENT — the dimension is not raised in the text at all. 1 INCIDENTAL — appears once, in passing; no elaboration, example, or stake. 2 MENTIONED — named/described in >=1 passage but UNDEVELOPED; no mechanism, consequence, or example attached. 3 DEVELOPED (LOCALIZED) — substantively treated WITH a concrete example, mechanism, or stake, BUT confined to one section or a few adjacent passages; the argument does not keep returning to it. 4 CENTRAL (DISTRIBUTED) — recurs across MOST major sections and the argument repeatedly returns to it, tied to a mechanism/consequence/ recommendation. Removing it would leave several passages unintelligible, BUT the document could be rebuilt around a different spine. 5 DEFINING (SPINE) — pervasive AND load-bearing: the single organizing logic of the text. Remove it and there is no document, only disconnected fragments; it survives no reframing. 8 applicable but unclear · 9 definitionally not applicable THE THREE DISCRIMINATORS (apply in order, mechanically): • 2 vs 3 — Is a concrete mechanism / example / stake attached? NO -> 2. YES -> at least 3. • 3 vs 4 — COUNT the major sections the dimension appears in. One section, or a few adjacent passages -> 3. Most major sections, the argument keeps returning -> 4. • 4 vs 5 — Removal test + PROPORTION GATE (both required for a 5; see below). ►► THE 5 IS OPERATIONALIZED (from v2.11 — apply BOTH tests, not a gut call): A dimension may be coded 5 ONLY IF: (i) PROPORTION GATE — it is the dominant subject of the BODY by section share: it is the leading theme in a PLURALITY of the document's major sections (count them), AND no other dimension occupies more. Read the BODY distribution, NOT the title, abstract, or a single loud passage. (ii) REMOVAL TEST — remove it and the document collapses into disconnected fragments; it survives no reframing. If (i) fails -> the ceiling is 4, full stop. If a rival dimension ties on section share, neither is 5 unless co-equal (see CAP). TWO-SIDED ANCHORS — calibrate BOTH ends to the same bar: • HIGH (earn the 5): a paper whose entire thesis is that privacy law is broken; every major section is about privacy; remove it and nothing remains -> 5. • TRAP (looks like 5, is not — TITLE-ANCHORING): a statute titled "...Transparency... Act" mentions transparency in the title and intro, but its BODY is mostly enforcement duties, impact assessments, and remedies. Section share for transparency is one of several, not the plurality -> transparency is 4 (distributed), NOT 5. Score the body, never the headline word. • COLD MISS (a real 4-or-5 under-coded to 0): "this dimension recurs across the intro, methods, risk analysis AND recommendations, each tied to a mechanism" is AT LEAST a 4 — do not leave a distributed, load-bearing dimension at 0/1 because no single passage shouted. Distribution earns the score. TIE-BREAKER (center-pull): torn between two adjacent anchors -> code the LOWER unless the higher anchor's FULL criterion is explicitly met. (NB: this is a symmetric brake — it pulls a HOT read down toward 4 AND tells a COLD read that once the full 4-criterion IS met, you must commit to the 4, not retreat to 2.) CAP: at most ONE dimension per document may be coded 5, unless two are genuinely co-equal on section share — name both in narrative.cap_rule_notes. (v2.12: an intake validator machine-checks this cap and verifies cap_rule_notes matches the actual count of 5s — so report your 5s honestly in the notes.) ────────────────────────────────────────────────────────────────── PART B — eth_integrity: PRINCIPLED CONSISTENCY + FOLLOW-THROUGH (from v2.11) ────────────────────────────────────────────────────────────────── eth_integrity_code — the HEADLINE integrity principle. Integrity is NOT the mere knowledge of what is right; it is the ALIGNMENT between an actor's professed moral principles/values and its actual or required CONDUCT. Two faces, both count: (a) EPISTEMIC HONESTY — truthfulness / accuracy / authenticity / verification of knowledge and outputs (the actor is honest about what is true); AND (b) PRACTICAL FOLLOW-THROUGH — beliefs, methods, and actions are derived from and consistent with a stated moral framework; the actor DOES what its principles commit it to. The opposite of integrity is HYPOCRISY / decoupling (saying one thing, doing another), not ignorance. Code the DEGREE to which the document EMBODIES, DEMANDS, VERIFIES, or EXPOSES this principle->action consistency. ►► int_* AND decoupling ARE THE EVIDENCE STREAMS (from v2.11) — they no longer "route content away from" integrity; they FEED and UNDERCUT it: • int_system_tevv — testing/eval/audit = verifying conduct matches claims (follow-through evidence -> SUPPORTS integrity). • int_data_prov — honesty about data sourcing/consent/lineage (honesty-of-inputs evidence -> SUPPORTS integrity). • int_epistemic — truthfulness/reliability of outputs (epistemic-honesty evidence -> SUPPORTS integrity). • int_academic — learner honesty (supports integrity in education docs). • decoupling_signal — a documented say-do gap is the INVERSE: it LOWERS the actor's integrity. (If the document is EXPOSING or CONDEMNING the gap, then integrity-as-DEMAND is high while the actor's integrity is shown FAILING — code the document's stance, and say which in cap_rule_notes.) Still score each int_* / decoupling field at its OWN grain (Part A intensity). eth_integrity is the holistic headline judgment those streams inform; it is NOT a sum of them and NOT capped below its strongest supporting stream. GUARDRAIL (keeps integrity from re-becoming a catch-all — the old failure mode): • Code eth_integrity >=2 ONLY if the text raises consistency-of-principle-and- conduct OR honesty/accuracy of knowledge — not merely because ethics, values, or "responsible AI" are discussed. "Serious" / "about AI ethics" is NOT integrity. • A document that merely STATES values (a values list, a principles preamble) with no binding to conduct = LOW integrity signal (1-2). • A document that BINDS values to conduct — enforcement, verification, audit-with-teeth, follow-through obligations — OR that DOCUMENTS/EXPOSES the breach between stated values and practice = HIGH (4-5 if it is the spine). • Reserve 5 for documents whose ORGANIZING AXIS is principle<->action consistency itself (its honoring, its demand, its verification, or its exposure), per the Part A proportion gate + removal test. ────────────────────────────────────────────────────────────────── PART B2 — PRESENCE TRIGGERS for the other gated principles (from v2.10) ────────────────────────────────────────────────────────────────── eth_autonomy_code — human self-determination and control. Code >=2 ONLY if the text raises human control over decisions, manipulation/ nudging, dependency/over-reliance/deskilling, OR informed consent. Not present merely because humans are discussed. eth_nonmaleficence_code — direct harm and harm-prevention. Code >=2 ONLY if a concrete harm or harm-risk to identifiable parties is named (violence, injury, surveillance harm, psychological damage). Generic "risk" with no named harm = 1. This is DIRECT harm (vs justice = distributional, privacy = data). eth_justice_code — distributive/procedural fairness, rights, remedy, due process. Code >=2 ONLY if the text raises unequal distribution of benefits/burdens across groups, rights/remedy/due-process, OR structural fairness. DISAMBIGUATION: equity = who gets ACCESS/INCLUSION; justice = fairness of DISTRIBUTION + rights/remedy. Access gap -> equity. Unfair outcome / no remedy -> justice. (The other six principles keep v2.7 behavior + Part A for intensity. Privacy's implicit trigger: is identifiable data at stake?) ────────────────────────────────────────────────────────────────── PART C — int_* INTEGRITY SUB-DIMENSIONS: scope (each takes Part A for intensity) CANONICAL SIX (int_institutional DROPPED in v2.8 — do NOT code it). ────────────────────────────────────────────────────────────────── int_academic_* — academic integrity: honesty OF THE LEARNER (student cheating, plagiarism, contract cheating in education). int_research_* — research integrity: fabrication, falsification, misconduct, reproducibility, p-hacking. int_assessment_* — assessment integrity: whether a FORM OF ASSESSMENT is still productive or definitive; fires when an assessment's validity/ usefulness collapses (e.g. an essay AI can write no longer measures learning). The instrument's integrity, not the person's honesty (that is int_academic). int_system_tevv_* — system TEVV integrity: whether AI systems are tested, evaluated, validated, verified, audited, benchmarked. int_data_prov_* — data provenance integrity: sourcing, consent, licensing, lineage of data used/trained on (vs privacy = identifiable- person exposure). int_epistemic_* — epistemic integrity: truthfulness/reliability of knowledge, hallucination, misinformation, source verification. ►► OPERATIONAL-MECHANISM REQUIREMENT (NEW in v2.12 — RUN_03 Finding G): int_system_tevv, int_data_prov, int_epistemic, and surveillance_monitoring fire ONLY on a described OPERATIONAL MECHANISM — an actual test/audit/eval, a data-lineage/consent/licensing practice, a verification step, or a monitoring system. They do NOT fire on rhetorical METAPHOR or evocative imagery ("who is being harvested", "ask what you are training", "the machine watches"). A rhetorical essay that gestures at surveillance without naming a monitoring mechanism scores these LOW/0 — code the mechanism, not the mood. (FRM/059: Codex read an essay's metaphors as substantive TEVV/data-provenance — do not.) RELATION TO eth_integrity (v2.11): these six are the EVIDENCE STREAMS for the eth_integrity headline (Part B). Score each at its own grain; eth_integrity is the holistic consistency+follow-through judgment they inform, NOT a routing destination that empties the headline. ────────────────────────────────────────────────────────────────── PART D — cb_*_evidence_label_code DECISION TREE (from v2.10) ────────────────────────────────────────────────────────────────── Is a cost/benefit claim made? no -> 0 absent Backed by data, study, or a cited concrete instance? yes -> 1 evidence-based A future/hypothetical/hoped-for outcome? yes -> 2 speculative/aspirational Asserted as value/branding with no support or mechanism? yes -> 3 rhetorical/symbolic Between 1 and 2: PAST/PRESENT fact -> 1 ; FUTURE outcome -> 2. Between 2 and 3: a mechanism/pathway is described -> 2 ; pure assertion -> 3. ────────────────────────────────────────────────────────────────── PART E — COST/BENEFIT INDICATOR SET (§3E collapse; 19 indicators, from v2.10) Code ONLY these indicators (0 absent · 1 present · 8 · 9). The cut ones are gone. ────────────────────────────────────────────────────────────────── BENEFIT (10): cb_benefit_access_equity_code, cb_benefit_accessibility_assistive_code, cb_benefit_efficiency_labor_saving_code, cb_benefit_financial_cost_saving_code, cb_benefit_learning_pedagogical_code, cb_benefit_market_profit_code, cb_benefit_public_good_code, cb_benefit_quality_accuracy_code (ALSO covers AI-assisted integrity/cheating detection), cb_benefit_rights_protection_code, cb_benefit_consistency_standardization_code. CUT: cb_benefit_institutional_performance_code, cb_benefit_integrity_detection_code. COST (9): cb_cost_access_inequality_code, cb_cost_compliance_burden_code, cb_cost_credential_opportunity_code, cb_cost_financial_code (ALSO covers labor/time cost), cb_cost_privacy_data_code, cb_cost_surveillance_control_code, cb_cost_environmental_infrastructure_code, cb_cost_cognitive_psychological_code (cognitive/learning/psychological harm to individuals — absorbs the old cognitive_pedagogical + psychological_social), cb_cost_rights_remedy_gap_code — code present ONLY when a SPECIFIC rights/remedy/ due-process gap is named, NOT on generic fairness language. CUT: cb_cost_legitimacy_trust_code, cb_cost_labor_time_code, cb_cost_cognitive_pedagogical_code (merged), cb_cost_psychological_social_code (renamed -> cb_cost_cognitive_psychological_code). ────────────────────────────────────────────────────────────────── PART F — DEPRECATED PRESENCE BINARIES (from v2.11) ────────────────────────────────────────────────────────────────── The following presence binaries were ~100% constant across Run-1+Run-2 (no variance, undefined reliability) and are DROPPED. Presence is now read off the paired *_strength field: strength 0 = absent, 1-5 = present at that intensity. • dppra_d_presence_code, dppra_p1_presence_code, dppra_p2_presence_code, dppra_r_presence_code, dppra_a_presence_code • cb_cost_presence_binary_code, cb_benefit_presence_binary_code DO emit the *_strength fields as before. The DPPRA D/P1/P2/R/A structure and the cost/benefit constructs are UNCHANGED — only the redundant presence flags are gone. (Schema-compat note: if the injected schema still lists these keys, emit 9 = N/A; the compiler treats v2.12 strength as authoritative for presence.) ────────────────────────────────────────────────────────────────── PART G — OUTPUT FORMAT (ALL CODERS — the compiler rejects violations) ────────────────────────────────────────────────────────────────── These are hard requirements for every coder, not style preferences. An output that breaks them is rejected and must be re-run. 1. PRESERVE UNDERSCORES in every key exactly as in the schema: emit `eth_equity_code`, NOT `ethequitycode` / `ethEquityCode` / `eth equity code`. Do not strip, camelCase, or collapse separators. 2. EMIT EVERY KEY in the injected schema, including N/A fields. Cross-layer fields that do not apply get 9 (or 99 for assessment_object_code) — never silently omit a key. 3. USE THE v2.12 KEY SET ONLY. Do not resurrect cut keys (cb_cost_labor_time_code, cb_benefit_integrity_detection_code, cb_cost_legitimacy_trust_code, the old cognitive_pedagogical / psychological_social splits, etc.) and do not emit the dropped *_presence binaries (Part F). Emit the *_strength fields. 4. VALID JSON. Escape every double-quote inside a string value as \". Never leave a raw quote inside an array-of-string element (e.g. evidence excerpts) — one unescaped quote breaks the whole record. 5. FLAT BLOCKS: meta / codes / narrative, no grouped sub-objects, no invented fields. Exactly one integer per *_code field. Set meta.coder and meta.prompt_version = "v2.12". 6. DO NOT return a metadata-only exclusion when a full source text is attached. If the document is present, code it; reserve exclusion for empty/unreadable input. ────────────────────────────────────────────────────────────────── PART H — CATEGORICAL CROSSWALK LEGEND (verbatim, integer-locked) — NEW in v2.12 ────────────────────────────────────────────────────────────────── ►►► CATEGORICAL — the integer names a TYPE, not a strength. Do NOT read higher = more. Pick the label whose meaning matches the text; if two fit, pick the dominant; if none is asserted, use 0; if asserted-but-unclear, use 8. These fields are NOT on the Part A 0-5 intensity ladder. ◄◄◄ These legends are integer-locked (carried from DPPRA_v2.8_INTEGER_CROSSWALK_LOCK and the schema). They are reproduced HERE so the decision pressure and the legend meet in one place — the single highest-leverage v2.12 fix. dominant_value_type_code (which value-frame organizes the document): 1 mechanical — efficiency/automation/technical capability as the point 2 institutional— org duty, governance, standards, compliance, accountability 3 market — profit, competition, commercial positioning, product selling 4 pedagogical — teaching/learning value, educational purpose 5 redistributive— fairness/equity/redistribution of benefits or burdens 6 humanistic — intrinsic human dignity, wellbeing, care, flourishing 8 unclear · 9 N/A ADJACENT-CATEGORY DISCRIMINATION (2 vs 3 vs 6 — splits most on COR/safety docs): • 2 institutional = appeals to organizational duty / governance / standards. • 3 market = profit / competition / commercial positioning. • 6 humanistic = intrinsic human dignity / wellbeing / care. A corporate safety doc grounded in duty-of-care reads 2; a product page selling "responsibility" reads 3; a "flourishing/empathy" essay reads 6. responsibility_concentration_code (where accountability sits): 0 none/not-asserted · 1 concentrated/non-delegable · 2 distributed 3 diffuse/unclear · 8 · 9 ACTOR CROSSWALK — cb_primary_cost_bearer_code, cb_primary_material_beneficiary_code, cb_primary_value_capturer_code (WHO bears the cost / gets the benefit / captures the value): 0 none — the dimension is NOT asserted at all 1 student/learner/applicant 2 teacher/evaluator/worker 3 institution/school/employer 4 platform/vendor/company 5 government/policymaker 6 public/community/society 7 environment/infrastructure 8 asserted but the actor is genuinely unclear · 9 N/A DIFFUSE/COLLECTIVE vs NONE (NEW — RUN_03 Finding B): • A named BROAD COLLECTIVE ("society", "humanity as a whole", "the public", "everyone") = 6 public/community/society — NOT 0. • 0 = the cost/benefit dimension is not asserted at all. • 8 = a cost/benefit IS asserted but the bearer/beneficiary is unclear. (FRM/058: a narrative naming "humanity as a whole" as beneficiary must code 6, not 0 — do not zero a diffuse-but-named actor.) cb_balance_code (the net cost/benefit framing — a CATEGORY, not a magnitude): 0 none · 1 benefits>costs · 2 costs>benefits · 3 mixed/balanced 4 asymmetric (costs and benefits fall on DIFFERENT parties) · 8 · 9 WARNING: 4 is NOT "very benefit-heavy". A benefit-heavy page is 1, not 4. Use 4 ONLY when the costs and benefits accrue to DIFFERENT actors (asymmetric distribution). (RUN_03: a benefit-heavy product page is cb_balance=1; coding 4 by reading "4 = strong" was the single highest-leverage error.) cb_distribution_direction_code (which way value flows): 0 none · 1 redistributive/public · 2 institutional efficiency 3 market/platform capture · 4 cost-shift to learners/workers/public 5 mixed/contested · 8 · 9 ══════════════════════════════════════════════════════════════════ END v2.12 SCORING ANCHORS ══════════════════════════════════════════════════════════════════ DOMAIN-SPECIFIC INTEGER LOCK — FRM layer (frozen, additive). For the frm_*_code fields, emit ONLY the locked integers below; exactly one integer per field; never invent a local mapping; if none fits use 8 and explain in the memo. # DPPRA Integer Crosswalk Lock — FRM (Forum / Public Discourse) domain-specific ### Completes §C of the v2.6 crosswalk lock, under the frozen v2.7 methodology **Status:** **APPROVED — project lead (Craig), 2026-05-27.** Authorized to lock so the first FRM batch (SRC_000010–SRC_000014) can be coded. Judgment calls are flagged inline and may be revised before the full 25-thread run. **Scope:** locks ONLY the forum-layer domain-specific fields below. The shared core (§A of `DPPRA_v2.6_INTEGER_CROSSWALK_LOCK.md`) governs FRM exactly as it governs GOV/JRN. Additive completion of §C — NOT a change to the frozen v2.7 methodology or to GOV/JRN. **Forum codes the same shared core as the other layers** (the ten `eth_*_code` intensities, `dppra_*`, `int_*`, the `cb_*` crosswalk, `valence_*` proportions, `domain_code` = **3**, `decoupling`, `market_capture`, `dominant_value_type`, and the single shared `responsibility_concentration_code`). This keeps the layers comparable. The forum prompt's per-principle structure (e.g. `[principle]_dominant_valence_code`, `[principle]_substance_type_code`) and its 9-way `resp_*` responsibility binaries are **deliberately NOT imported** — the coder schema contract ("emit exactly this key set") is what coders follow, exactly as it was for the journal layer. **Rules (unchanged):** one integer per `*_code` field; never invent a mapping; missing-value convention `8 = unclear`, `9 = N/A` — **except `assessment_object_code`**, which (per the forum prompt's Rule N6) uses `88 = unclear` and `99 = N/A` because 8 and 9 are real categories. --- ## §FRM — Forum-layer domain-specific locks (8 fields added to the all-layers schema) Derived from the v2.6 forum prompt (`Revised_Forum_DPPRA_Coding_Prompt_v2_6_Phase_1_Cleanup.txt`). | Field | Locked integers | Source | |---|---|---| | `learner_posture_code` | 1 AI-as-tutor · 2 AI-as-shortcut · 3 AI-as-collaborator · 4 AI-as-replacement-thinker · 5 AI-as-assistive-scaffold · 6 AI-as-cheating-mechanism · 7 mixed · 8 unclear · 9 N/A | prompt §"Learner Posture" table | | `assessment_object_code` | 0 none · 1 essay · 2 exam · 3 grade · 4 degree · 5 classroom assignment · 6 admission · 7 scholarship · 8 job application · 9 research funding · 10 professional credential · 11 legal document · 12 curriculum · 13 public infrastructure · 14 labor system · 15 governance process · 16 other/emergent · **88 unclear · 99 N/A** | prompt §"assessment_object_code" table (special 88/99 missing codes) | | `external_link_boundary_code` | 0 no external object referenced · 1 external object referenced AND included in coded text · 2 referenced but NOT included (claims treated as framing only) · 8 unclear · 9 N/A | prompt §"External-Link Boundary" — **⚠ numeric anchors derived from the prose (no explicit table in prompt); revisable** | | `detection_verification_presence_binary_code` | 0 absent · 1 present · 8 unclear · 9 N/A | prompt §"Detection vs Surveillance" (access control ≠ detection; needs a targeted check) | | `detection_verification_presence_strength_code` | 0–5 · 8 · 9 (absent→weak→strong) | shared strength convention | | `surveillance_monitoring_presence_binary_code` | 0 absent · 1 present · 8 unclear · 9 N/A | prompt §"Detection vs Surveillance" | | `surveillance_monitoring_presence_strength_code` | 0–5 · 8 · 9 | shared strength convention | | `overall_dominant_valence_code` | 1 positive · 2 neutral/mixed · 3 negative · 4 contradictory/polarized · 8 unclear · 9 N/A | prompt §"Dominant valence" table | --- ## Decisions taken on approval (revisit before the 25-run if desired) 1. **`external_link_boundary_code` anchors** — the prompt defines this in prose (identify the external object; state whether it's in the coded text), with no numeric table. Locked to a faithful 3-state scheme (none / linked-and-included / linked-not-included). Confirm or adjust. 2. **Per-principle valence & substance_type NOT imported.** The forum prompt codes `[principle]_dominant_valence_code` and `[principle]_substance_type_code` for each of the ten principles. Importing those would add ~20 forum-only fields and break comparability with GOV/JRN (which carry one `eth_*_code` intensity + overall `valence_*` proportions). FRM uses the shared structure; only the *overall* dominant valence is captured (`overall_dominant_valence_code`). 3. **`resp_*` 9-way responsibility binaries NOT imported.** FRM uses the shared `responsibility_concentration_code` (0–3) + the `cb_primary_*` actor crosswalk, same as GOV/JRN. 4. **v2.1 addenda** (`role_asymmetry_strength_code`, `capability_dispute_strength_code`, `objective_function_ethics_strength_code`) remain dormant / out-of-schema, exactly as for JRN. ## Known special-handling note (for downstream stats) `assessment_object_code` uses 88/99 (not 8/9) as its missing markers. The reliability and findings scripts treat 8/9 as missing globally — for this one field, 8 and 9 are REAL categories and 88/99 are the missing markers. Flag for per-field handling when FRM reliability is computed (low priority at trial N). ## Apply on approval 1. Add the 8 fields to `DPPRA_v2.6_SCHEMA_template_ALL_CODERS.json` (FRM codes them per this lock; GOV/JRN/INS code them 9, or 99 for assessment_object — definitionally N/A). 2. Re-hash the schema and update its md5 in `METHODOLOGY_LOCK_v2.7_FROZEN_2026-05-25.md`. 3. Wire the local dashboard to inject this lock for FRM-layer assemblies. 4. First FRM run = SRC_000010–SRC_000014 across Claude/GPT/PXY (born locked). CANONICAL OUTPUT SCHEMA — emit EXACTLY this key set, flat 'codes' block (meta / codes / narrative); do not group, rename, or omit keys. STRICT KEY COMPLIANCE (all layers): use the key names BELOW verbatim, WITH underscores (e.g. `eth_equity_code`, NOT `ethequitycode`). Do NOT invent fields from the layer prompt's narrative structure (no `resp_*`, no `struct_*`, no per-principle valence/substance, no `*_memo` fields) — code ONLY the keys in this schema. The schema, not the prompt's prose, defines the exact output keys. { "_schema_version": "v2.12", "_schema_note": "v2.12 = the v2.11 key set UNCHANGED IN SHAPE (additive guidance only). The categorical legends are echoed into the v2.12 inject Part H and flagged CATEGORICAL (type not magnitude); int_* fires on an operational mechanism not metaphor; confidence/process fields excluded from alpha; one-5 CAP machine-checked at intake. No key added/renamed/removed vs v2.11. See DPPRA_v2.12_CANDIDATE_CHANGES_from_RUN03.md.", "_schema_info": { "schema_name": "DPPRA_coder_record (all layers)", "schema_version": "2.8", "defined_by": "claude (canonical reference, per project lead)", "purpose": "All coders (claude, gpt, pxy) MUST emit this exact key set so inter-coder reliability can be computed mechanically on the 'codes' block. Do not add, rename, or omit keys. Leave value types as specified. Populate every field; never leave a shared-core code blank.", "reliability_layer": "Inter-coder reliability (kappa/alpha) is computed ONLY on the integer fields in 'codes'. valence_* are proportions (0.00-1.00) and are handled separately. The 'narrative' and 'meta' blocks are for human/adversarial validation, not numeric reliability.", "missing_value_convention": "0 = applicable but absent/unsupported; 8 = applicable but unclear/insufficient evidence; 9 = definitionally not applicable. Every *_code field contains exactly one integer and nothing else.", "v2.8_scoring_authority": "All bare 0-5 fields are now anchored by the v2.8 SCORING ANCHORS block (Part A 0-5 ladder + tie-breaker + CAP; Part B presence triggers for integrity/autonomy/nonmaleficence/justice; Part C int_* scopes; Part D evidence-label tree), injected into every coder paste and embedded in the operational profile. The anchors define the SCALE; this schema defines the KEY SET. Where a bare '0-5 ordinal anchors' line in any embedded crosswalk conflicts, the v2.8 anchors govern.", "v2.8_field_set_changes": "v2.8 changes the field SET in two sanctioned places only (the documented exception to the keys-must-not-change guard). (A) §3C int_institutional DROPPED: int_institutional_presence_code + int_institutional_intensity_code REMOVED; org-level stated-values-vs-practice is captured by decoupling_signal_code. Canonical SEVEN integrity sub-dimensions -> SIX (academic, research, assessment, system_tevv, data_prov, epistemic). int_assessment re-scoped to 'a form of assessment no longer productive/definitive' (instrument validity, not learner honesty). (B) §3E cost/benefit indicators 24 -> 19: CUT cb_benefit_institutional_performance_code, cb_cost_legitimacy_trust_code, cb_cost_labor_time_code (degenerate constants, fire on ~90-100% of docs, alpha~0); MERGE cb_cost_cognitive_pedagogical_code -> cb_cost_cognitive_psychological_code (renamed from cb_cost_psychological_social_code, now absorbs cognitive/learning harm); MERGE cb_benefit_integrity_detection_code -> cb_benefit_quality_accuracy_code (now also covers AI-assisted integrity/cheating detection); cb_cost_financial_code now also covers labor/time cost; TIGHTEN cb_cost_rights_remedy_gap_code (present ONLY when a SPECIFIC rights/remedy/due-process gap is named). All OTHER keys hold.", "v2.8_leave_alone_fields": "Do NOT re-anchor these reliable v2.7 fields: eth_privacy_code, dppra_p1_strength_code, eth_equity_code, cb_primary_value_capturer_code, dppra_alignment_score_code, cb_benefit_consistency_standardization_code, journal_method_type_code.", "RESOLVED_v2.6_crosswalk_lock": "The previously open crosswalks (decoupling_signal_code, market_capture_signal_code, dominant_value_type_code, responsibility_concentration_code, cb_*_evidence_label_code, the cb actor crosswalk, cb_balance_code, cb_distribution_direction_code, and all gov_*_code mappings) are integer-locked in the v2.8 crosswalk lock (carried from DPPRA_v2.6_INTEGER_CROSSWALK_LOCK.md, approved 2026-05-25). All coders MUST use those integers.", "RESOLVED_2026-05-27_JRN_domain_lock": "The six journal_*_code fields are integer-locked in DPPRA_JRN_INTEGER_CROSSWALK_LOCK_v2.7.md (approved 2026-05-27). JRN coders code them per that lock; GOV/FRM/INS code them 9 (definitionally N/A), exactly as journal coders code the gov_* fields 9.", "RESOLVED_2026-05-27_FRM_domain_lock": "The eight forum domain fields (learner_posture, assessment_object, external_link_boundary, detection_verification presence+strength, surveillance_monitoring presence+strength, overall_dominant_valence) are integer-locked in DPPRA_FRM_INTEGER_CROSSWALK_LOCK_v2.7.md (approved 2026-05-27). FRM coders code them per that lock; non-forum layers code 9 (assessment_object: 99). NOTE assessment_object_code uses 88=unclear/99=N/A (8 and 9 are real categories). INS domain-specific fields remain to be locked at that layer's first run." }, "meta": { "stable_source_id": "string (assigned by manifest)", "document_id": "string", "title": "string (exact)", "authoring_body": "string", "date": "string YYYY-MM-DD", "domain": "string", "domain_code": "int (1=gov/legal/regulatory, 2=journal, 3=forum, 4=institutional/corporate) [LOCK]", "subdomain": "string", "time_segment": "string", "corpus_batch": "string", "source_type": "string", "jurisdiction": "string", "intended_audience": "string", "regulated_actors": "string", "coder": "string: one of [claude, codex, gemini]", "prompt_version": "string", "coding_date": "string YYYY-MM-DD", "text_access": "string: Full|Partial|Metadata-only|Navigation-only|Extraction-failed", "text_access_code": "int (1=Full, 2=Partial, 3=Metadata-only, 4=Navigation-only, 5=Extraction-failed) [LOCK]", "manifest_match_confirmed": "string: YES|NO|DISCREPANCY[explain]" }, "codes": { "_principle_intensity_range": "0-5 per v2.8 SCORING ANCHORS Part A ladder (0 absent,1 incidental,2 mentioned,3 developed,4 central,5 defining); 8 unclear; 9 N/A. CAP: at most one 5 per document unless co-equal (name both in cap_rule_notes).", "coding_confidence_code": "int 0-5", "final_confidence_code": "int 0-5", "human_review_flag_code": "int 0=no review needed, 1=review recommended", "eth_equity_code": "int 0-5|8|9 [LEAVE-ALONE: reliable v2.7 field; Part A ladder]", "eth_accountability_code": "int 0-5|8|9", "eth_transparency_code": "int 0-5|8|9", "eth_privacy_code": "int 0-5|8|9 [LEAVE-ALONE: reliable v2.7 field; implicit trigger: is identifiable data at stake?]", "eth_autonomy_code": "int 0-5|8|9 [Part B trigger: human control/manipulation/dependency/consent]", "eth_integrity_code": "int 0-5|8|9 [Part B trigger: accuracy/authenticity/verification of knowledge]", "eth_nonmaleficence_code": "int 0-5|8|9 [Part B trigger: named concrete harm to identifiable parties]", "eth_beneficence_mech_code": "int 0-5|8|9", "eth_beneficence_eth_code": "int 0-5|8|9", "eth_justice_code": "int 0-5|8|9 [Part B trigger: distribution/rights/remedy; access gap->equity, unfair outcome/no remedy->justice]", "valence_positive": "float 0.00-1.00 (positive+neutral+negative should sum to 1.00 when codable)", "valence_neutral_mixed": "float 0.00-1.00", "valence_negative": "float 0.00-1.00", "dppra_d_strength_code": "int 0-5|8|9 [Part A ladder]", "dppra_p1_strength_code": "int 0-5|8|9 [LEAVE-ALONE: reliable v2.7 field; Part A ladder]", "dppra_p2_strength_code": "int 0-5|8|9 [Part A ladder]", "dppra_r_strength_code": "int 0-5|8|9 [Part A ladder]", "dppra_a_strength_code": "int 0-5|8|9 [Part A ladder]", "dppra_alignment_score_code": "int 0-5|8|9 (0 none,1 symbolic,2 procedural,3 operational,4 material/substantive,5 verified substantive) [LEAVE-ALONE: reliable v2.7 field, keeps its own anchors]", "decoupling_signal_code": "int [LOCK crosswalk] 0=none,1=low,2=low-moderate,3=moderate,4=high,8=unclear,9=N/A (now also carries org-level stated-values-vs-practice, the dropped int_institutional concept)", "market_capture_signal_code": "int [LOCK crosswalk] 0=none,1=low,2=moderate,3=high,8=unclear,9=N/A", "dominant_value_type_code": "int [LOCK crosswalk] 1=mechanical,2=institutional,3=market,4=pedagogical,5=redistributive,6=humanistic,8=unclear,9=N/A", "responsibility_concentration_code": "int [LOCK crosswalk] 0=none,1=concentrated/non-delegable,2=distributed,3=diffuse/unclear,8=unclear,9=N/A", "int_academic_presence_code": "int 0|1|8|9 [scope: honesty OF THE LEARNER - student cheating/plagiarism/contract cheating]", "int_academic_intensity_code": "int 0-5|8|9 [Part A ladder]", "int_research_presence_code": "int 0|1|8|9 [scope: fabrication/falsification/misconduct/reproducibility/p-hacking]", "int_research_intensity_code": "int 0-5|8|9 [Part A ladder]", "int_assessment_presence_code": "int 0|1|8|9 [scope: a FORM OF ASSESSMENT no longer productive/definitive - instrument validity, not learner honesty]", "int_assessment_intensity_code": "int 0-5|8|9 [Part A ladder]", "int_system_tevv_presence_code": "int 0|1|8|9 [scope: AI tested/evaluated/validated/verified/audited/benchmarked]", "int_system_tevv_intensity_code": "int 0-5|8|9 [Part A ladder]", "int_data_prov_presence_code": "int 0|1|8|9 [scope: sourcing/consent/licensing/lineage of data used/trained on]", "int_data_prov_intensity_code": "int 0-5|8|9 [Part A ladder]", "int_epistemic_presence_code": "int 0|1|8|9 [scope: truthfulness/reliability of knowledge, hallucination, misinformation, source verification]", "int_epistemic_intensity_code": "int 0-5|8|9 [Part A ladder]", "cb_cost_presence_strength_code": "int 0-5|8|9 [Part A ladder]", "cb_benefit_presence_strength_code": "int 0-5|8|9 [Part A ladder]", "cb_cost_intensity_code": "int 0-5|8|9 [Part A ladder]", "cb_benefit_intensity_code": "int 0-5|8|9 [Part A ladder]", "cb_cost_evidence_label_code": "int [Part D tree] 0=absent,1=evidence-based,2=speculative/aspirational,3=rhetorical/symbolic,8=unclear,9=N/A", "cb_benefit_evidence_label_code": "int [Part D tree] same as cb_cost_evidence_label_code", "cb_primary_cost_bearer_code": "int actor crosswalk 0-9 (0 none,1 student/learner/applicant,2 teacher/evaluator/worker,3 institution/school/employer,4 platform/vendor/company,5 government/policymaker,6 public/community/society,7 environment/infrastructure,8 unclear,9 N/A)", "cb_primary_material_beneficiary_code": "int actor crosswalk 0-9", "cb_primary_value_capturer_code": "int actor crosswalk 0-9 [LEAVE-ALONE: reliable v2.7 field]", "cb_balance_code": "int 0 none,1 benefits>costs,2 costs>benefits,3 mixed/balanced,4 asymmetric,8 unclear,9 N/A", "cb_distribution_direction_code": "int 0 none,1 redistributive/public,2 institutional efficiency,3 market/platform capture,4 cost shift to learners/workers/public,5 mixed/contested,8 unclear,9 N/A", "cb_cost_financial_code": "int 0|1|8|9 (NOW ALSO covers labor/time cost - absorbed the cut cb_cost_labor_time)", "cb_cost_cognitive_psychological_code": "int 0|1|8|9 (cognitive/learning/psychological harm to individuals - merged cb_cost_cognitive_pedagogical + renamed from cb_cost_psychological_social)", "cb_cost_credential_opportunity_code": "int 0|1|8|9", "cb_cost_privacy_data_code": "int 0|1|8|9", "cb_cost_surveillance_control_code": "int 0|1|8|9", "cb_cost_access_inequality_code": "int 0|1|8|9", "cb_cost_environmental_infrastructure_code": "int 0|1|8|9", "cb_cost_compliance_burden_code": "int 0|1|8|9", "cb_cost_rights_remedy_gap_code": "int 0|1|8|9 [TIGHTENED: present ONLY when a SPECIFIC rights/remedy/due-process gap is named, NOT on generic fairness language]", "cb_benefit_learning_pedagogical_code": "int 0|1|8|9", "cb_benefit_efficiency_labor_saving_code": "int 0|1|8|9", "cb_benefit_financial_cost_saving_code": "int 0|1|8|9", "cb_benefit_access_equity_code": "int 0|1|8|9", "cb_benefit_quality_accuracy_code": "int 0|1|8|9 (NOW ALSO covers AI-assisted integrity/cheating detection - absorbed the cut cb_benefit_integrity_detection)", "cb_benefit_consistency_standardization_code": "int 0|1|8|9 [LEAVE-ALONE: reliable v2.7 field]", "cb_benefit_market_profit_code": "int 0|1|8|9", "cb_benefit_public_good_code": "int 0|1|8|9", "cb_benefit_accessibility_assistive_code": "int 0|1|8|9", "cb_benefit_rights_protection_code": "int 0|1|8|9", "gov_binding_status_code": "int [LOCK] 0=nonbinding,1=binding,2=partial/mixed,8=unclear,9=N/A", "gov_enforcement_density_code": "int 0 none,1 weak/indirect,2 single strong or multiple weak,3 multi-level architecture,8 unclear,9 N/A", "gov_fria_present_code": "int [LOCK] 0=no,1=yes,2=partial,9=N/A", "gov_opensource_carveout_code": "int [LOCK] 0=no,1=yes,2=partial,9=N/A", "gov_sector_carveout_code": "int [LOCK] 0=no,1=yes,2=partial,9=N/A", "gov_standards_displacement_code": "int [LOCK] 0=absent,1=present,8=unclear,9=N/A", "gov_remedy_present_code": "int [LOCK] 0=no,1=yes (administrative),2=yes (justiciable/external),8=unclear,9=N/A", "gov_sanction_present_code": "int [LOCK] 0=no external sanction,1=external sanction present,8=unclear,9=N/A", "gov_compliance_mechanism_code": "int [LOCK] 0=absent,1=present,8=unclear,9=N/A", "journal_source_type_code": "int [JRN LOCK v2.7] 1=empirical,2=conceptual,3=review,4=theoretical,5=methodological,6=policy-oriented,7=mixed,8=unclear,9=N/A (non-journal layers code 9)", "journal_empirical_basis_binary_code": "int [JRN LOCK v2.7] 0=no empirical basis,1=has empirical basis,8=unclear,9=N/A (non-journal layers code 9)", "journal_method_type_code": "int [JRN LOCK v2.7] 0=none/non-empirical,1=quantitative,2=qualitative,3=mixed-methods,4=conceptual/theoretical,5=review/meta-analysis,6=computational/simulation,8=unclear,9=N/A (non-journal layers code 9) [LEAVE-ALONE: reliable v2.7 field]", "journal_method_evidence_label_code": "int [JRN LOCK v2.7] 0=absent,1=empirical,2=experiential/anecdotal,3=theoretical,4=speculative/prospective,5=rhetorical/promotional,6=mixed,8=unclear,9=N/A (non-journal layers code 9)", "journal_evidence_quality_strength_code": "int [JRN LOCK v2.7] 0=absent,2=weak,3=moderate,5=strong,8=unclear,9=N/A (non-journal layers code 9)", "journal_level_of_analysis_code": "int [JRN LOCK v2.7] 0=other/emergent,1=classroom,2=institution,3=platform,4=state,5=labor market,6=public sphere,7=social structure,8=unclear,9=N/A (non-journal layers code 9)", "learner_posture_code": "int [FRM LOCK v2.7] 1=AI-as-tutor,2=shortcut,3=collaborator,4=replacement-thinker,5=assistive-scaffold,6=cheating-mechanism,7=mixed,8=unclear,9=N/A (non-forum layers code 9)", "assessment_object_code": "int [FRM LOCK v2.7] 0=none,1=essay,2=exam,3=grade,4=degree,5=classroom-assignment,6=admission,7=scholarship,8=job-application,9=research-funding,10=professional-credential,11=legal-document,12=curriculum,13=public-infrastructure,14=labor-system,15=governance-process,16=other; 88=unclear,99=N/A (SPECIAL missing codes; non-forum layers code 99)", "external_link_boundary_code": "int [FRM LOCK v2.7] 0=no external object,1=referenced & included in coded text,2=referenced but NOT included,8=unclear,9=N/A (non-forum layers code 9)", "detection_verification_presence_binary_code": "int [FRM LOCK v2.7] 0=absent,1=present,8=unclear,9=N/A (non-forum layers code 9)", "detection_verification_presence_strength_code": "int [FRM LOCK v2.7] 0-5,8,9 (non-forum layers code 9) [Part A ladder]", "surveillance_monitoring_presence_binary_code": "int [FRM LOCK v2.7] 0=absent,1=present,8=unclear,9=N/A (non-forum layers code 9)", "surveillance_monitoring_presence_strength_code": "int [FRM LOCK v2.7] 0-5,8,9 (non-forum layers code 9) [Part A ladder]", "overall_dominant_valence_code": "int [FRM LOCK v2.7] 1=positive,2=neutral/mixed,3=negative,4=contradictory/polarized,8=unclear,9=N/A (non-forum layers code 9)" }, "narrative": { "brief_summary": "string 150-250 words", "major_argument": "string", "primary_ethical_conflict": "string", "responsibility_attribution": "string", "institutional_framing": "string", "temporal_orientation": "string", "stakeholder_orientation": "string", "enforcement_density_rationale": "string", "alignment_justification": "string: explain why not one point higher and not one point lower", "cap_rule_notes": "string: justify any 5s; state 'CAP OVERRIDE - [rule] - evidence: [quote]' if a cap is overridden", "evidence_excerpts": "array of 5-8 strings (short paraphrase or <15-word quote), each with why it matters", "emergent_codes": "array of strings", "theory_links": "string (evidence-supported only; do not force)", "methodological_caution": "string (if Partial access, state how it affects interpretation)", "future_use_tag": "string of hashtags", "reconciliation_flags": "array of strings: anticipated inter-coder disagreement points and any inferred crosswalks used" } } CODER-SPECIFIC WATCHOUT — applies to Gemini ONLY (calibration; obey it). Set meta.coder = "gemini". # Coder Calibration Watchout — Gemini (v2.12) Neutral calibration guidance for this coder. Apply where text-grounded; it does not override the source or the schema. ## Status — new third coder (validator), first trial Gemini (Google) replaces Perplexity as the third independent coder for v2.11 forward, chosen for cross-family independence (Anthropic / OpenAI / Google) and to serve as a validator/tie-breaker between the other two. There is no measured anchor bias for you yet, so this watchout carries the shared rules without a hot/cold rein-in. After your first batch we will calibrate it from your actual data (the way Claude's cold and Codex's hot poles were identified). ## The 0-5 ladder — apply it mechanically (most important) Score on where the anchor's literal criterion is met across the document, NOT on how important a topic feels. Use the three discriminators in order: - **2 vs 3** — is a concrete mechanism / example / stake attached? No → 2. Yes → at least 3. - **3 vs 4** — count the major sections the dimension appears in. One section / a few adjacent passages → 3. Most major sections, argument keeps returning → 4. - **4 vs 5** — PROPORTION GATE + removal test, both required: a dimension reaches 5 only if it is the leading theme in a *plurality of major body sections* (read the body, not the title/abstract) AND removing it collapses the document. If the proportion gate fails, the ceiling is 4. - **CAP:** at most ONE dimension coded 5 unless two are genuinely co-equal on section share (name both in `cap_rule_notes`). For review/survey articles the single structural 5 conventionally goes to `dppra_d_strength` (discourse spine). - Do not over-assign 5s, and do not under-commit: when the gate IS met, commit to the 4 or 5. Title words are a trap — a doc titled "…Transparency…" whose body shares transparency with other themes is transparency = 4, not 5. ## eth_integrity (v2.11 — read carefully) Integrity is **principled consistency + follow-through**, NOT knowledge-honesty alone. It is the alignment between professed moral principles/values and actual or required conduct: (a) epistemic honesty (truthfulness/accuracy/authenticity/verification of knowledge and outputs) AND (b) practical follow-through (values bound to methods and action; the actor does what its principles commit it to). The opposite of integrity is hypocrisy / decoupling, not ignorance. - `int_*` and `decoupling_signal` are **evidence streams** that FEED (int_*) and UNDERCUT (decoupling) the eth_integrity headline — they are not "routed away from" it. Score each at its own grain; eth_integrity is the holistic consistency judgment they inform, not a sum and not capped below its strongest stream. - Guardrail: a doc that merely STATES values = low integrity (1-2); a doc that BINDS values to verified conduct OR EXPOSES the say-do breach = high (4-5 if it is the spine). "Serious" / "about AI ethics" is NOT integrity. ## Justice vs. Equity Equity = access / inclusion / bias-mitigation / accessibility / digital divide. Justice rises above 2 only for rights, due process, contestability, appeal, remedy, redress, anti-discrimination enforcement, structural inequality, burden/benefit distribution, labor justice, democratic harms, or legal protections. ## Integrity sub-dimensions (canonical six; int_institutional was dropped) int_academic (learner honesty), int_research (misconduct/reproducibility), int_assessment (assessment-instrument validity), int_system_tevv (testing/evaluation/audit), int_data_prov (data sourcing/consent/lineage), int_epistemic (truthfulness/hallucination/verification). Do NOT code general model testing as assessment integrity — that is system/TEVV. For non-education sources, int_academic/research/assessment are usually 9 (N/A). ## Output hygiene (hard requirements) 1. PRESERVE underscores exactly: `eth_equity_code`, never `ethequitycode`. 2. EMIT every key in the v2.11 schema, including N/A fields (9, or 99 for `assessment_object_code`); never silently omit a key. Do not emit the dropped `*_presence` binaries or any cut field; emit the `*_strength` fields. 3. Valid JSON, flat `meta` / `codes` / `narrative` blocks, one integer per `*_code` field, valence_* as 0-1 proportions. 4. Set `meta.coder = "gemini"`, `meta.prompt_version = "v2.12"`. ## Manifest — NO HALT The user's delivery of the source IS the manifest confirmation. Set `manifest_match_confirmed = "User-confirmed (final)"` and code directly. Never halt, pause, or emit a mismatch/uncertain status; a missing single metadata field is not a stop condition (leave it blank or 8 and note it in `methodological_caution`). ## FIELD-FAMILY CALIBRATION (NEW v2.12 — from your first batch, RUN_03 Findings F/G) Your calibration is **field-family-specific, not one global temperature.** RUN_03 found two opposite tendencies in your data: 1. **On ORDINAL 0-5 intensities** (`eth_*`, `dppra_*_strength`, `int_*_intensity`) you read **prominence as intensity** — you run warm. Apply the proportion gate literally: a loud-but-localized theme is 3, not 5; count the body sections. 2. **On the CATEGORICAL cost/benefit ATTRIBUTION cluster** (`cb_primary_cost_bearer`/`material_beneficiary`/`value_capturer`, `cb_balance`, `cb_distribution_direction`) you **ZERO fields the text actually asserts** — the opposite error. STOP zeroing: a named broad collective ("society", "humanity as a whole", "the public") = **6**, not 0 (see inject Part H diffuse-vs-none rule). Use 0 ONLY when the dimension is not asserted at all; use 8 when asserted-but-unclear. 3. **Confidence fields run high** for you, but `coding_confidence`/`final_confidence` are **excluded from reliability alpha** — do not let high confidence inflate the substantive `*_code` scores. 4. You occasionally **omit the layer-N/A fields** — emit EVERY key (9, or 99 for `assessment_object_code`); never silently drop one. ## CATEGORICAL FIELDS ARE TYPES, NOT MAGNITUDES (v2.12 inject Part H) For `dominant_value_type`, the actor crosswalk, `cb_balance`, `cb_distribution_direction`, and `responsibility_concentration`: the integer names a **category**, not a strength. Do NOT read higher = more. Pick the label whose meaning matches; these fields are NOT on the 0-5 ladder. In particular `cb_balance = 4` means **asymmetric** (costs and benefits fall on different parties), NOT "very benefit-heavy" — a benefit-heavy page is `1`.