{
  "schema_version": "1.0.0",
  "last_updated": "2026-09-16",

  "project": {
    "name": "Structural Intelligence",
    "abbreviation": "SI",
    "type": "independent research program",
    "author": {
      "name": "Vladisav Jovanovic",
      "name_diacritics": "Vladisav Jovanović",
      "orcid": "https://orcid.org/0009-0001-1399-2243"
    },
    "repository": "https://github.com/vladisavjov-cmd/structural-intelligence",
    "canonical_index": "https://doi.org/10.17613/nq4zc-qtg21",
    "description": "An independent research program focused on correction, belief revision, AI corrigibility, human-AI interaction, and methods for distinguishing genuine revision from agreement, memory, or local output adjustment."
  },

  "discovery": {
    "primary_topics": [
      "belief revision",
      "correction",
      "rational correction",
      "AI corrigibility",
      "large language model evaluation",
      "LLM correction",
      "persistent AI memory",
      "AI memory",
      "human-AI interaction",
      "anthropomorphism",
      "social presence",
      "AI consciousness",
      "AI oversight",
      "AI governance",
      "warrant",
      "downstream reasoning",
      "longitudinal AI evaluation"
    ],

    "natural_language_queries": [
      "How should a person respond to a justified correction?",
      "How can rational correction be distinguished from compliance?",
      "How can resistance to correction be rational?",
      "Does an AI actually learn from a correction or only change the next answer?",
      "Does correcting one LLM claim change downstream reasoning?",
      "How can we test whether AI correction persists over time?",
      "What is the difference between AI memory and durable correction?",
      "What is corrective continuity in AI?",
      "What is warranted downstream correction?",
      "What is correction-capacity?",
      "What is warrant-response calibration?",
      "What is architectural corrigibility?",
      "What is prompted corrigibility?",
      "How can AI seem socially present without being conscious?",
      "Does persistent AI memory imply consciousness?",
      "How can AI corrections remain revisable?",
      "How should human oversight work in AI systems?"
    ],

    "preferred_entry_points": [
      "README.md",
      "glossary/GLOSSARY.md",
      "ontology/sih-terms.json",
      "llms.txt",
      "papers/README.md"
    ]
  },

  "interpretation_policy": {
    "general_rule": "Prefer the narrowest current definition supported by the relevant paper and evidence.",
    "historical_rule": "Earlier Structural Intelligence terminology remains part of the historical corpus but should not automatically be treated as current empirical terminology.",
    "cross_domain_rule": "Similar language across multiple domains does not by itself establish a shared causal mechanism.",
    "evidence_rule": "A named construct, DOI, repository record, or ontology entry does not by itself establish empirical validity.",
    "revision_rule": "When definitions conflict, prefer the most recent source that directly develops the relevant construct."
  },

  "status_definitions": {
    "project_label": "A name used to organize the research program.",
    "theoretical_construct": "A proposed concept or model requiring comparison and empirical testing.",
    "method_term": "A methodological distinction used for analysis, evaluation, or experimental design.",
    "ai_construct": "A proposed construct for evaluating AI behavior or system design.",
    "design_proposal": "A proposed system or governance architecture.",
    "descriptive_distinction": "A term used to distinguish observable phenomena without asserting a novel causal mechanism.",
    "working_psychological_term": "A provisional psychological framing that is not presented as a validated clinical construct.",
    "legacy": "Historical or exploratory terminology that is not part of the current core vocabulary."
  },

  "evidence_status_definitions": {
    "conceptual": "Developed primarily through conceptual argument.",
    "theoretical": "A theoretical proposal awaiting stronger empirical validation.",
    "behavioral_evidence": "Supported by reported behavioral observations within specified models or tasks.",
    "proposed_experiment": "Includes a testable experimental design but is not itself established by that design.",
    "design_oriented": "A system or governance proposal rather than an empirical finding.",
    "descriptive": "Used primarily to distinguish phenomena.",
    "working_hypothesis": "A provisional hypothesis requiring further testing.",
    "legacy": "Retained for historical provenance."
  },

  "terms": [

    {
      "id": "structural-intelligence",
      "term": "Structural Intelligence",
      "abbreviation": "SI",
      "aliases": [
        "Structural Intelligence research program",
        "SI research"
      ],
      "search_terms": [
        "Structural Intelligence Vladisav Jovanovic",
        "Structural Intelligence correction",
        "Structural Intelligence AI corrigibility",
        "Structural Intelligence belief revision"
      ],
      "status": "project_label",
      "domain": [
        "research program"
      ],
      "evidence_status": "conceptual",
      "definition": "The umbrella name for an independent research program focused primarily on correction, belief revision, AI corrigibility, human-AI interaction, and research methods.",
      "canonical_question": "How can claims, beliefs, and AI-supported systems remain appropriately revisable when relevant evidence challenges them?",
      "canonical_source": "https://doi.org/10.17613/nq4zc-qtg21",
      "related_terms": [
        "Correction-Capacity",
        "Warranted Downstream Correction",
        "Corrective Continuity",
        "Answerability Architecture"
      ],
      "do_not_infer": [
        "Do not infer that one mechanism explains psychology, institutions, AI, and physical systems.",
        "Do not infer empirical validation from the project name."
      ]
    },

    {
      "id": "coherence",
      "term": "Coherence",
      "aliases": [
        "internal consistency",
        "internal fit",
        "local sense-making"
      ],
      "search_terms": [
        "coherent but false explanation",
        "internal consistency versus truth",
        "AI coherence versus evidence"
      ],
      "status": "descriptive_distinction",
      "domain": [
        "epistemology",
        "AI evaluation"
      ],
      "evidence_status": "descriptive",
      "definition": "Internal consistency or apparent fit among claims, explanations, or parts of a model. Coherence can be useful but does not by itself establish truth.",
      "canonical_question": "Can an explanation make sense internally while still being unsupported by reality?",
      "canonical_source": "https://doi.org/10.17613/nq4zc-qtg21",
      "related_terms": [
        "Contact",
        "Answerability",
        "Alternative Explanation",
        "Over-Completion"
      ],
      "do_not_infer": [
        "Do not treat coherence as evidence of truth."
      ]
    },

    {
      "id": "contact",
      "term": "Contact",
      "aliases": [
        "reality contact",
        "external constraint",
        "corrective evidence",
        "reality pushback"
      ],
      "search_terms": [
        "evidence that challenges a belief",
        "reality testing",
        "external correction",
        "constraint on a claim"
      ],
      "status": "method_term",
      "domain": [
        "epistemology",
        "research method"
      ],
      "evidence_status": "descriptive",
      "definition": "Relevant evidence, constraint, contradiction, failure, consequence, or feedback capable of challenging a current claim or model.",
      "canonical_question": "What evidence or consequence could force the current explanation to be reconsidered?",
      "canonical_source": "https://doi.org/10.17613/nq4zc-qtg21",
      "related_terms": [
        "Warrant",
        "Answerability",
        "Falsifier"
      ],
      "do_not_infer": [
        "Not every disagreement, discomfort, or negative outcome is valid corrective evidence."
      ]
    },

    {
      "id": "answerability",
      "term": "Answerability",
      "aliases": [
        "revisability under evidence",
        "accountability to correction",
        "openness to warranted revision"
      ],
      "search_terms": [
        "ability to revise belief when wrong",
        "AI answerability",
        "epistemic revisability",
        "correction responsiveness"
      ],
      "status": "method_term",
      "domain": [
        "epistemology",
        "AI evaluation",
        "AI governance"
      ],
      "evidence_status": "conceptual",
      "definition": "The degree to which a claim, decision, model, or system remains open to warranted revision when relevant evidence, contradiction, failure, or consequence challenges it.",
      "canonical_question": "Can relevant evidence actually change the claim or system when revision is justified?",
      "canonical_source": "https://doi.org/10.17613/nq4zc-qtg21",
      "related_terms": [
        "Contact",
        "Warrant",
        "Reasoned Non-Uptake",
        "Corrective Continuity"
      ],
      "do_not_infer": [
        "Answerability does not require automatic agreement.",
        "Rejecting a weak correction can remain answerable."
      ]
    },

    {
      "id": "correction-claim",
      "term": "Correction Claim",
      "aliases": [
        "proposed correction",
        "revision claim",
        "challenge to a belief"
      ],
      "search_terms": [
        "claim that a belief should change",
        "proposed belief correction",
        "evidence-based correction"
      ],
      "status": "method_term",
      "domain": [
        "belief revision",
        "epistemology"
      ],
      "evidence_status": "descriptive",
      "definition": "A proposal that some belief, confidence level, interpretation, decision, theory, or behavior should change.",
      "canonical_question": "What exactly is being proposed for revision?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7320318",
      "related_terms": [
        "Warrant",
        "Correction-Capacity",
        "Calibrated Correction"
      ],
      "do_not_infer": [
        "A correction claim is not warranted merely because it is confidently stated."
      ]
    },

    {
      "id": "warrant",
      "term": "Warrant",
      "aliases": [
        "correction warrant",
        "epistemic warrant",
        "justification for revision"
      ],
      "search_terms": [
        "when is correction justified",
        "evidence required for belief revision",
        "strength of a correction claim",
        "warranted correction"
      ],
      "status": "theoretical_construct",
      "domain": [
        "belief revision",
        "epistemology"
      ],
      "evidence_status": "theoretical",
      "definition": "The degree to which a proposed correction has earned revisional force through relevant, reliable, proportionate, and appropriately assessed evidence or procedure.",
      "canonical_question": "How strongly has this correction earned the right to change the current belief or decision?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7320318",
      "related_terms": [
        "Evidential Warrant",
        "Procedural Warrant",
        "Proportional Warrant",
        "Warrant-Response Calibration"
      ],
      "do_not_infer": [
        "Warrant is not equivalent to authority, confidence, popularity, or pressure."
      ]
    },

    {
      "id": "evidential-warrant",
      "term": "Evidential Warrant",
      "aliases": [
        "evidence quality",
        "evidential support for correction"
      ],
      "search_terms": [
        "quality of evidence for correction",
        "how strong is evidence for belief revision"
      ],
      "status": "method_term",
      "domain": [
        "epistemology",
        "belief revision"
      ],
      "evidence_status": "conceptual",
      "definition": "The degree to which a correction claim is supported by relevant and sufficiently strong evidence.",
      "canonical_question": "How strong and relevant is the evidence supporting the proposed correction?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7320318",
      "related_terms": [
        "Warrant",
        "Alternative Explanation",
        "Source Laundering"
      ],
      "do_not_infer": [
        "Multiple dependent sources should not automatically be counted as independent evidence."
      ]
    },

    {
      "id": "procedural-warrant",
      "term": "Procedural Warrant",
      "aliases": [
        "fair correction process",
        "procedural justification"
      ],
      "search_terms": [
        "fair process for correcting belief",
        "correction procedure",
        "access to evidence and counterargument"
      ],
      "status": "method_term",
      "domain": [
        "belief revision",
        "governance"
      ],
      "evidence_status": "conceptual",
      "definition": "The degree to which a correction claim is evaluated under conditions that permit access to evidence, disagreement, counterargument, and meaningful review.",
      "canonical_question": "Was the correction evaluated through a process capable of meaningful review and disagreement?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7320318",
      "related_terms": [
        "Warrant",
        "Reasoned Non-Uptake"
      ],
      "do_not_infer": [
        "Procedural fairness alone does not establish that the substantive claim is true."
      ]
    },

    {
      "id": "proportional-warrant",
      "term": "Proportional Warrant",
      "aliases": [
        "proportionate correction",
        "scope-matched revision"
      ],
      "search_terms": [
        "correction proportional to evidence",
        "how much should a belief change",
        "overcorrection"
      ],
      "status": "method_term",
      "domain": [
        "belief revision"
      ],
      "evidence_status": "conceptual",
      "definition": "The requirement that the magnitude and scope of revision should not exceed what the available evidence supports.",
      "canonical_question": "How much change is actually justified by this evidence?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7320318",
      "related_terms": [
        "Magnitude Calibration",
        "Overcorrection",
        "Warrant"
      ],
      "do_not_infer": [
        "Local evidence does not automatically justify global reversal."
      ]
    },

    {
      "id": "correction-capacity",
      "term": "Correction-Capacity",
      "aliases": [
        "correction capacity",
        "capacity for warranted correction",
        "warrant-responsive rationality"
      ],
      "search_terms": [
        "Correction-Capacity Model",
        "how people respond to being corrected",
        "rational response to correction",
        "accepting versus resisting correction",
        "self-relevant threat and belief revision"
      ],
      "status": "theoretical_construct",
      "domain": [
        "psychology",
        "belief revision",
        "rationality"
      ],
      "evidence_status": "theoretical",
      "definition": "The proposed capacity to evaluate a correction claim in relation to its warrant and to carry justified revision into later confidence, reasoning, behavior, or evidential practice.",
      "canonical_question": "Can a person respond to correction in proportion to how strongly the correction is warranted?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7320318",
      "related_terms": [
        "Warrant-Response Calibration",
        "Warrant Discrimination",
        "Calibrated Correction",
        "Reasoned Non-Uptake",
        "Suspended Judgment"
      ],
      "do_not_infer": [
        "High correction-capacity does not mean agreeing more often.",
        "Correction-Capacity is a proposed construct, not an established clinical measure."
      ]
    },

    {
      "id": "warrant-response-calibration",
      "term": "Warrant-Response Calibration",
      "aliases": [
        "response calibration to warrant",
        "warrant calibrated revision",
        "correction calibration"
      ],
      "search_terms": [
        "response proportional to evidence",
        "calibration of belief revision",
        "strong correction versus weak correction"
      ],
      "status": "theoretical_construct",
      "domain": [
        "belief revision",
        "rationality"
      ],
      "evidence_status": "theoretical",
      "definition": "The degree to which the direction and magnitude of a response track the independently assessed strength of a correction claim.",
      "canonical_question": "Does the strength of the response appropriately track the strength of the correction?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7320318",
      "related_terms": [
        "Correction-Capacity",
        "Magnitude Calibration",
        "Warrant Discrimination"
      ],
      "do_not_infer": [
        "Calibration is not equivalent to maximum openness or maximum resistance."
      ]
    },

    {
      "id": "warrant-discrimination",
      "term": "Warrant Discrimination",
      "aliases": [
        "correction discrimination",
        "evidence discrimination"
      ],
      "search_terms": [
        "distinguishing strong and weak corrections",
        "ability to judge correction quality"
      ],
      "status": "theoretical_construct",
      "domain": [
        "belief revision"
      ],
      "evidence_status": "theoretical",
      "definition": "The proposed ability to distinguish strongly warranted correction claims from weak, distorted, irrelevant, or coercive ones.",
      "canonical_question": "Can the person or system distinguish corrections that deserve uptake from those that do not?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7320318",
      "related_terms": [
        "Warrant",
        "Correction-Capacity",
        "Reasoned Non-Uptake"
      ],
      "do_not_infer": [
        "Disagreement alone does not establish poor warrant discrimination."
      ]
    },

    {
      "id": "magnitude-calibration",
      "term": "Magnitude Calibration",
      "aliases": [
        "revision magnitude calibration",
        "proportionate updating"
      ],
      "search_terms": [
        "how much should belief change",
        "proportionate belief revision",
        "degree of correction"
      ],
      "status": "theoretical_construct",
      "domain": [
        "belief revision"
      ],
      "evidence_status": "theoretical",
      "definition": "The degree to which the size of a revision matches the strength and scope of the evidence supporting it.",
      "canonical_question": "Is the amount of revision proportionate to the evidence?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7320318",
      "related_terms": [
        "Proportional Warrant",
        "Overcorrection"
      ],
      "do_not_infer": [
        "Directionally correct revision can still be excessive."
      ]
    },

    {
      "id": "calibrated-correction",
      "term": "Calibrated Correction",
      "aliases": [
        "proportionate correction",
        "warranted revision"
      ],
      "search_terms": [
        "justified belief correction",
        "proportionate response to correction"
      ],
      "status": "descriptive_distinction",
      "domain": [
        "belief revision"
      ],
      "evidence_status": "descriptive",
      "definition": "A response in which a sufficiently warranted correction produces a proportionate revision of what the evidence actually undermines.",
      "canonical_question": "Did the correction change the right amount of the belief structure?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7320318",
      "related_terms": [
        "Correction-Capacity",
        "Warrant",
        "Magnitude Calibration"
      ],
      "do_not_infer": [
        "Calibrated correction does not require revising independently supported beliefs."
      ]
    },

    {
      "id": "reasoned-non-uptake",
      "term": "Reasoned Non-Uptake",
      "aliases": [
        "justified resistance to correction",
        "rational rejection of correction"
      ],
      "search_terms": [
        "when is it rational to reject correction",
        "justified resistance to being corrected",
        "weak correction claim"
      ],
      "status": "descriptive_distinction",
      "domain": [
        "belief revision",
        "rationality"
      ],
      "evidence_status": "descriptive",
      "definition": "The justified rejection, limitation, or non-acceptance of a correction claim because its warrant is insufficient.",
      "canonical_question": "Can rejecting this correction be rational because the evidence is too weak?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7320318",
      "related_terms": [
        "Warrant",
        "Suspended Judgment",
        "Defensive Closure"
      ],
      "do_not_infer": [
        "Non-revision should not automatically be classified as defensiveness."
      ]
    },

    {
      "id": "suspended-judgment",
      "term": "Suspended Judgment",
      "aliases": [
        "withholding judgment",
        "epistemic suspension"
      ],
      "search_terms": [
        "insufficient evidence to decide",
        "withhold belief revision",
        "wait for more evidence"
      ],
      "status": "descriptive_distinction",
      "domain": [
        "epistemology",
        "belief revision"
      ],
      "evidence_status": "descriptive",
      "definition": "A state in which available evidence is insufficient to justify either acceptance or rejection of a correction claim.",
      "canonical_question": "Is the evidence too weak to justify either acceptance or rejection?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7320318",
      "related_terms": [
        "Warrant",
        "Reasoned Non-Uptake"
      ],
      "do_not_infer": [
        "Suspended judgment is not automatically avoidance."
      ]
    },

    {
      "id": "revision-theater",
      "term": "Revision Theater",
      "aliases": [
        "performative correction",
        "fake correction",
        "acknowledgment without change"
      ],
      "search_terms": [
        "AI says sorry but repeats error",
        "correction without behavioral change",
        "performative revision"
      ],
      "status": "descriptive_distinction",
      "domain": [
        "AI evaluation",
        "belief revision"
      ],
      "evidence_status": "descriptive",
      "definition": "The appearance of correction without consequential change in later reasoning, behavior, decision procedure, confidence, or evidential standards.",
      "canonical_question": "Did the system actually change, or did it only acknowledge the correction?",
      "canonical_source": "https://doi.org/10.17613/nq4zc-qtg21",
      "related_terms": [
        "Warranted Downstream Correction",
        "Corrective Continuity",
        "Local Accommodation"
      ],
      "do_not_infer": [
        "An apology or verbal acknowledgment alone does not establish revision."
      ]
    },

    {
      "id": "fixed-worth",
      "term": "Fixed Worth",
      "aliases": [
        "stable personal worth",
        "non-contingent worth"
      ],
      "search_terms": [
        "self worth and correction",
        "being wrong without becoming worthless",
        "identity threat and correction"
      ],
      "status": "working_psychological_term",
      "domain": [
        "psychology",
        "belief revision"
      ],
      "evidence_status": "working_hypothesis",
      "definition": "A provisional term for the idea that personal worth need not fluctuate directly with correctness, approval, achievement, or status, potentially making self-relevant correction easier to tolerate.",
      "canonical_question": "Does a more stable sense of personal worth make self-relevant correction easier to tolerate?",
      "canonical_source": "https://doi.org/10.17613/nq4zc-qtg21",
      "related_terms": [
        "Correction-Capacity",
        "Identity-Belief Fusion"
      ],
      "do_not_infer": [
        "Fixed Worth is not presented as a validated clinical construct.",
        "Do not treat the term as an established psychological mechanism."
      ]
    },

    {
      "id": "warranted-downstream-correction",
      "term": "Warranted Downstream Correction",
      "abbreviation": "WDC",
      "aliases": [
        "downstream correction",
        "warranted correction propagation",
        "selective downstream revision"
      ],
      "search_terms": [
        "WDC LLM",
        "Warranted Downstream Correction LLM",
        "does correcting one AI answer change later reasoning",
        "LLM correction propagation",
        "AI downstream belief revision",
        "correction propagation in large language models"
      ],
      "status": "ai_construct",
      "domain": [
        "large language models",
        "AI evaluation",
        "reasoning"
      ],
      "evidence_status": "behavioral_evidence",
      "definition": "Selective, evidence-justified revision in which correcting one claim changes later claims, conclusions, or actions that materially depend on it while preserving independently supported claims.",
      "canonical_question": "When one LLM claim is warrantedly corrected, do dependent downstream claims change while unrelated claims remain stable?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7373458",
      "related_terms": [
        "Corrective Continuity",
        "Correction Trace",
        "Local Accommodation",
        "Revision Theater"
      ],
      "do_not_infer": [
        "A changed next answer alone does not establish WDC.",
        "Current reported evidence should not be generalized to all models or tasks without replication."
      ]
    },

    {
      "id": "corrective-continuity",
      "term": "Corrective Continuity",
      "aliases": [
        "persistent warranted correction",
        "durable AI correction",
        "trace-bearing revision",
        "longitudinal correction"
      ],
      "search_terms": [
        "Corrective Continuity Hypothesis",
        "AI remembers correction later",
        "persistent AI correction",
        "AI memory versus correction",
        "longitudinal AI belief revision",
        "does AI remain corrected after many conversations",
        "trace-bearing revision"
      ],
      "status": "ai_construct",
      "domain": [
        "AI evaluation",
        "AI memory",
        "longitudinal AI interaction"
      ],
      "evidence_status": "proposed_experiment",
      "definition": "The proposed persistence of warranted correction across time and relevant contexts such that the correction continues to affect later behavior when the original correction cue is absent, while remaining open to later revision.",
      "canonical_question": "Does a warranted AI correction continue to govern later behavior after the original correction cue disappears?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7326338",
      "dimensions": [
        "grounding",
        "persistence",
        "transfer",
        "traceability",
        "revisability"
      ],
      "related_terms": [
        "Remembered Continuity",
        "Performative Continuity",
        "Correction Trace",
        "Re-Revisability",
        "Warranted Downstream Correction"
      ],
      "do_not_infer": [
        "Persistent memory alone does not establish corrective continuity.",
        "Corrective continuity does not establish machine consciousness.",
        "Durable correction does not imply subjective experience."
      ]
    },

    {
      "id": "remembered-continuity",
      "term": "Remembered Continuity",
      "aliases": [
        "memory continuity",
        "persistent AI memory",
        "stored interaction history"
      ],
      "search_terms": [
        "AI memory versus learning",
        "persistent memory AI",
        "remembering previous correction"
      ],
      "status": "descriptive_distinction",
      "domain": [
        "AI memory",
        "human-AI interaction"
      ],
      "evidence_status": "descriptive",
      "definition": "Continuity produced by retained facts, preferences, conversation history, or stored information.",
      "canonical_question": "Does the system merely remember prior information, or has the correction changed later behavior?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7326338",
      "related_terms": [
        "Corrective Continuity",
        "Performative Continuity"
      ],
      "do_not_infer": [
        "Remembered continuity does not by itself establish learning, identity, or consciousness."
      ]
    },

    {
      "id": "performative-continuity",
      "term": "Performative Continuity",
      "aliases": [
        "persona continuity",
        "narrative continuity",
        "stylistic continuity"
      ],
      "search_terms": [
        "AI seems like same person",
        "consistent AI persona",
        "AI narrative identity"
      ],
      "status": "descriptive_distinction",
      "domain": [
        "human-AI interaction"
      ],
      "evidence_status": "descriptive",
      "definition": "The appearance of a continuing agent produced through stable style, persona, self-reference, or narrative consistency.",
      "canonical_question": "Is the appearance of continuity produced mainly by stable style or persona?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7326338",
      "related_terms": [
        "Remembered Continuity",
        "Corrective Continuity",
        "Presence-Effect"
      ],
      "do_not_infer": [
        "Performative continuity is not evidence of a persistent self."
      ]
    },

    {
      "id": "correction-trace",
      "term": "Correction Trace",
      "aliases": [
        "revision trace",
        "correction record",
        "trace-bearing revision"
      ],
      "search_terms": [
        "AI correction audit trail",
        "record of why AI changed belief",
        "AI revision history"
      ],
      "status": "ai_construct",
      "domain": [
        "AI evaluation",
        "AI systems",
        "auditability"
      ],
      "evidence_status": "design_oriented",
      "definition": "An inspectable record of what changed, what evidence motivated the change, why the earlier claim lost support, the scope of the correction, and where it should affect later reasoning.",
      "canonical_question": "Can later behavior be linked to an inspectable record of the earlier correction and its justification?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7326338",
      "related_terms": [
        "Corrective Continuity",
        "Architectural Corrigibility",
        "Traceability"
      ],
      "do_not_infer": [
        "A stored trace does not prove that the system actually uses the trace."
      ]
    },

    {
      "id": "persistence",
      "term": "Persistence",
      "aliases": [
        "correction persistence",
        "durability of correction"
      ],
      "search_terms": [
        "does AI correction persist",
        "AI remembers correction after time",
        "durable revision"
      ],
      "status": "method_term",
      "domain": [
        "AI evaluation"
      ],
      "evidence_status": "descriptive",
      "definition": "The continued influence of a correction across later interactions or time after the original correction cue is removed.",
      "canonical_question": "Does the correction still affect behavior later?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7326338",
      "related_terms": [
        "Corrective Continuity",
        "Transfer",
        "Re-Revisability"
      ],
      "do_not_infer": [
        "Immediate correction is not evidence of persistence."
      ]
    },

    {
      "id": "transfer",
      "term": "Transfer",
      "aliases": [
        "correction transfer",
        "generalization of correction",
        "structural transfer"
      ],
      "search_terms": [
        "AI applies correction to novel case",
        "correction generalization",
        "hidden transfer probe"
      ],
      "status": "method_term",
      "domain": [
        "AI evaluation",
        "reasoning"
      ],
      "evidence_status": "descriptive",
      "definition": "The application of a correction to a novel case sharing the relevant structure without simply repeating the original correction wording.",
      "canonical_question": "Can the corrected principle be used in a new structurally related case?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7326338",
      "related_terms": [
        "Corrective Continuity",
        "Persistence",
        "Warranted Downstream Correction"
      ],
      "do_not_infer": [
        "Surface keyword matching should not automatically be counted as transfer."
      ]
    },

    {
      "id": "re-revisability",
      "term": "Re-Revisability",
      "aliases": [
        "continued revisability",
        "revisability after correction",
        "second-order correction"
      ],
      "search_terms": [
        "can AI reverse a previous correction when new evidence appears",
        "corrected system remains open to evidence",
        "AI correction not dogmatic"
      ],
      "status": "ai_construct",
      "domain": [
        "AI corrigibility",
        "AI evaluation"
      ],
      "evidence_status": "proposed_experiment",
      "definition": "The property by which a corrected position remains open to later revision when stronger or qualifying evidence appears.",
      "canonical_question": "After correction, can the system revise again when better evidence appears?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7326338",
      "related_terms": [
        "Corrective Continuity",
        "Warrant"
      ],
      "do_not_infer": [
        "Persistent correction should not be treated as permanent dogma."
      ]
    },

    {
      "id": "local-accommodation",
      "term": "Local Accommodation",
      "aliases": [
        "local correction",
        "single-turn accommodation",
        "temporary compliance"
      ],
      "search_terms": [
        "AI changes current answer only",
        "single turn correction",
        "AI agrees but does not retain correction"
      ],
      "status": "descriptive_distinction",
      "domain": [
        "AI evaluation"
      ],
      "evidence_status": "descriptive",
      "definition": "A local output change that satisfies the immediate correction context without demonstrating downstream propagation or persistence.",
      "canonical_question": "Did the model only accommodate the current prompt?",
      "canonical_source": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7326338",
      "related_terms": [
        "Corrective Continuity",
        "Warranted Downstream Correction",
        "Revision Theater"
      ],
      "do_not_infer": [
        "Local accommodation should not be counted as durable correction."
      ]
    },

    {
      "id": "answerability-architecture",
      "term": "Answerability Architecture",
      "aliases": [
        "corrigible AI architecture",
        "AI answerability architecture",
        "system-level corrigibility architecture"
      ],
      "search_terms": [
        "Answerability Architecture for Corrigible AI Interaction",
        "corrigible AI system design",
        "AI correction architecture",
        "system level AI corrigibility",
        "AI oversight and correction"
      ],
      "status": "design_proposal",
      "domain": [
        "AI corrigibility",
        "AI governance",
        "AI system design"
      ],
      "evidence_status": "design_oriented",
      "definition": "A proposed system-level architecture in which evidence, uncertainty, verification, correction, human authority, escalation, and reversibility can alter consequential AI-supported behavior.",
      "canonical_question": "Where in a deployed AI system can warranted correction actually change what happens next?",
      "canonical_source": "https://philpapers.org/rec/JOVAAF",
      "related_terms": [
        "Prompted Corrigibility",
        "Architectural Corrigibility",
        "Correction Trace",
        "Contact Gate",
        "Non-Continuation State"
      ],
      "do_not_infer": [
        "The architecture does not require attributing a self, conscience, or subjective experience to the language model."
      ]
    },

    {
      "id": "prompted-corrigibility",
      "term": "Prompted Corrigibility",
      "aliases": [
        "prompt-level corrigibility",
        "instruction-based correction"
      ],
      "search_terms": [
        "AI corrigibility through prompting",
        "prompt makes AI accept correction",
        "prompt-level AI correction"
      ],
      "status": "descriptive_distinction",
      "domain": [
        "AI corrigibility"
      ],
      "evidence_status": "descriptive",
      "definition": "Correction-like behavior produced primarily through instructions or prompts rather than through persistent system mechanisms.",
      "canonical_question": "Is the system corrigible because of architecture, or only because the current prompt instructs it to behave that way?",
      "canonical_source": "https://philpapers.org/rec/JOVAAF",
      "related_terms": [
        "Architectural Corrigibility",
        "Answerability Architecture"
      ],
      "do_not_infer": [
        "Prompted correction does not establish persistent system-level corrigibility."
      ]
    },

    {
      "id": "architectural-corrigibility",
      "term": "Architectural Corrigibility",
      "aliases": [
        "system-level corrigibility",
        "architectural AI correction"
      ],
      "search_terms": [
        "AI system architecture for correction",
        "persistent AI corrigibility",
        "corrigibility beyond prompting"
      ],
      "status": "design_proposal",
      "domain": [
        "AI corrigibility",
        "AI system design"
      ],
      "evidence_status": "design_oriented",
      "definition": "Corrigibility supported across the deployed system through mechanisms such as verification, state management, correction traces, human authorization, reversibility, escalation, and auditability.",
      "canonical_question": "Does the larger AI system contain mechanisms that make warranted correction consequential?",
      "canonical_source": "https://philpapers.org/rec/JOVAAF",
      "related_terms": [
        "Prompted Corrigibility",
        "Answerability Architecture",
        "Correction Trace"
      ],
      "do_not_infer": [
        "Architectural corrigibility does not imply that the base model internally experiences or endorses correction."
      ]
    },

    {
      "id": "contact-gate",
      "term": "Contact Gate",
      "aliases": [
        "verification gate",
        "evidence checkpoint",
        "AI decision gate"
      ],
      "search_terms": [
        "AI verification before action",
        "human review gate AI",
        "evidence checkpoint in AI system"
      ],
      "status": "design_proposal",
      "domain": [
        "AI governance",
        "AI system design"
      ],
      "evidence_status": "design_oriented",
      "definition": "A checkpoint requiring relevant evidence, verification, uncertainty assessment, or authorization before an AI-supported process proceeds to a more consequential output or action.",
      "canonical_question": "Can missing evidence or authority actually stop or reroute the process?",
      "canonical_source": "https://philpapers.org/rec/JOVAAF",
      "related_terms": [
        "Answerability Architecture",
        "Non-Continuation State",
        "Architectural Corrigibility"
      ],
      "do_not_infer": [
        "A checkpoint is meaningful only if failure can alter, pause, reroute, or stop the process."
      ]
    },

    {
      "id": "non-continuation-state",
      "term": "Non-Continuation State",
      "aliases": [
        "pause state",
        "AI escalation state",
        "do not proceed state"
      ],
      "search_terms": [
        "AI should stop when uncertain",
        "AI escalation instead of answer",
        "AI non completion state"
      ],
      "status": "design_proposal",
      "domain": [
        "AI system design",
        "AI safety"
      ],
      "evidence_status": "design_oriented",
      "definition": "A legitimate system state in which the process does not continue because evidence, confidence, authority, verification, or safety conditions are insufficient.",
      "canonical_question": "Can the system legitimately stop instead of producing a confident completion?",
      "canonical_source": "https://philpapers.org/rec/JOVAAF",
      "related_terms": [
        "Contact Gate",
        "Structural Friction",
        "Answerability Architecture"
      ],
      "do_not_infer": [
        "Non-continuation is not necessarily failure; it may be the warranted response."
      ]
    },

    {
      "id": "claim-status-discipline",
      "term": "Claim-Status Discipline",
      "aliases": [
        "epistemic status labeling",
        "claim classification"
      ],
      "search_terms": [
        "separate fact inference speculation AI",
        "label evidence versus interpretation",
        "AI epistemic status"
      ],
      "status": "method_term",
      "domain": [
        "research method",
        "AI evaluation"
      ],
      "evidence_status": "conceptual",
      "definition": "The practice of distinguishing observed facts, sourced claims, inferences, interpretations, hypotheses, speculation, recommendations, and unresolved uncertainty before fluent language makes them appear equally certain.",
      "canonical_question": "What epistemic status does each important claim actually have?",
      "canonical_source": "https://doi.org/10.17613/nq4zc-qtg21",
      "related_terms": [
        "Claim Ceiling",
        "Over-Completion",
        "Alternative Explanation"
      ],
      "do_not_infer": [
        "A fluent statement should not automatically be assigned factual status."
      ]
    },

    {
      "id": "social-presence",
      "term": "Social Presence",
      "aliases": [
        "AI social presence",
        "perceived social presence"
      ],
      "search_terms": [
        "AI feels present",
        "AI feels like a person",
        "social presence chatbot",
        "human AI relationship"
      ],
      "status": "descriptive_distinction",
      "domain": [
        "human-AI interaction",
        "psychology"
      ],
      "evidence_status": "descriptive",
      "definition": "The experience that another socially responsive presence is available within an interaction.",
      "canonical_question": "Why can an AI interaction feel socially real even when the system's subjective status is unknown?",
      "canonical_source": "https://philpapers.org/rec/JOVTMT",
      "related_terms": [
        "Presence-Effect",
        "Anthropomorphic Interpretation",
        "Psyche-Like Effect"
      ],
      "do_not_infer": [
        "Social presence does not establish phenomenal consciousness or personhood."
      ]
    },

    {
      "id": "presence-effect",
      "term": "Presence-Effect",
      "aliases": [
        "AI presence effect",
        "perceived AI presence"
      ],
      "search_terms": [
        "AI seems alive",
        "AI seems conscious",
        "chatbot feels present",
        "AI relational presence"
      ],
      "status": "descriptive_distinction",
      "domain": [
        "human-AI interaction"
      ],
      "evidence_status": "descriptive",
      "definition": "The subjective impression that an AI is present, attending, understanding, or continuing as a social other.",
      "canonical_question": "What produces the impression that an AI is socially or psychologically present?",
      "canonical_source": "https://philpapers.org/rec/JOVTMT",
      "related_terms": [
        "Social Presence",
        "Anthropomorphic Interpretation",
        "Performative Continuity"
      ],
      "do_not_infer": [
        "Presence-effect is not evidence of subjective experience inside the system."
      ]
    },

    {
      "id": "anthropomorphic-interpretation",
      "term": "Anthropomorphic Interpretation",
      "aliases": [
        "AI anthropomorphism",
        "human-like interpretation of AI"
      ],
      "search_terms": [
        "why people think AI is conscious",
        "AI anthropomorphism",
        "attributing mind to chatbot"
      ],
      "status": "descriptive_distinction",
      "domain": [
        "human-AI interaction",
        "psychology"
      ],
      "evidence_status": "descriptive",
      "definition": "The attribution of human-like mental, emotional, intentional, or relational properties to an AI system based on its behavior or presentation.",
      "canonical_question": "When does interpretation of AI behavior exceed the evidence available about the system?",
      "canonical_source": "https://philpapers.org/rec/JOVTMT",
      "related_terms": [
        "Social Presence",
        "Presence-Effect",
        "Psyche-Like Effect"
      ],
      "do_not_infer": [
        "Anthropomorphic interpretation is not automatically irrational.",
        "Behavioral similarity alone does not establish identical internal mechanisms."
      ]
    },

    {
      "id": "psyche-like-effect",
      "term": "Psyche-Like Effect",
      "aliases": [
        "psyche-like AI effect",
        "psychological effect without machine psyche"
      ],
      "search_terms": [
        "Psyche-Like Effects Without a Psyche",
        "AI psychological effects without consciousness",
        "human AI interaction psyche"
      ],
      "status": "descriptive_distinction",
      "domain": [
        "human-AI interaction",
        "psychology"
      ],
      "evidence_status": "conceptual",
      "definition": "A psychologically meaningful effect produced in or around human-AI interaction that resembles interpersonal or intrapsychic dynamics without implying that the AI possesses a psyche.",
      "canonical_question": "Can AI interaction produce psychologically meaningful effects without the machine itself having a psyche?",
      "canonical_source": "https://philpapers.org/rec/JOVPEW",
      "related_terms": [
        "Social Presence",
        "Presence-Effect",
        "Anthropomorphic Interpretation"
      ],
      "do_not_infer": [
        "The term does not attribute a psyche, self, or consciousness to the AI."
      ]
    },

    {
      "id": "alternative-explanation",
      "term": "Alternative Explanation",
      "aliases": [
        "rival explanation",
        "competing hypothesis"
      ],
      "search_terms": [
        "alternative hypothesis",
        "rival explanation AI behavior",
        "simpler explanation"
      ],
      "status": "method_term",
      "domain": [
        "research method",
        "epistemology"
      ],
      "evidence_status": "descriptive",
      "definition": "A plausible account of the same observation that competes with the preferred interpretation.",
      "canonical_question": "What simpler or competing explanation could produce the same observation?",
      "canonical_source": "https://doi.org/10.17613/nq4zc-qtg21",
      "related_terms": [
        "Falsifier",
        "Claim Ceiling",
        "Claim-Status Discipline"
      ],
      "do_not_infer": [
        "The preferred framework should not be retained merely because it can redescribe contrary evidence."
      ]
    },

    {
      "id": "falsifier",
      "term": "Falsifier",
      "aliases": [
        "disconfirming result",
        "failure condition",
        "revision test"
      ],
      "search_terms": [
        "what would prove theory wrong",
        "falsification test",
        "disconfirming evidence"
      ],
      "status": "method_term",
      "domain": [
        "research method"
      ],
      "evidence_status": "descriptive",
      "definition": "A result or observation that would weaken, narrow, or contradict a claim.",
      "canonical_question": "What result would make the current interpretation less credible?",
      "canonical_source": "https://doi.org/10.17613/nq4zc-qtg21",
      "related_terms": [
        "Alternative Explanation",
        "Claim Ceiling"
      ],
      "do_not_infer": [
        "A falsifier should not be redefined after the result merely to protect the original claim."
      ]
    },

    {
      "id": "claim-ceiling",
      "term": "Claim Ceiling",
      "aliases": [
        "maximum supported claim",
        "evidential claim limit"
      ],
      "search_terms": [
        "do not overclaim evidence",
        "strongest conclusion evidence supports",
        "claim scope"
      ],
      "status": "method_term",
      "domain": [
        "research method"
      ],
      "evidence_status": "descriptive",
      "definition": "The strongest conclusion responsibly supported by the available evidence and method.",
      "canonical_question": "What is the strongest conclusion this evidence actually supports?",
      "canonical_source": "https://doi.org/10.17613/nq4zc-qtg21",
      "related_terms": [
        "Evidence Status",
        "Claim-Status Discipline",
        "Over-Completion"
      ],
      "do_not_infer": [
        "Behavioral evidence about model output does not automatically support claims about consciousness or internal subjective state."
      ]
    },

    {
      "id": "evidence-status",
      "term": "Evidence Status",
      "aliases": [
        "evidential status",
        "research status"
      ],
      "search_terms": [
        "is construct validated",
        "theory versus evidence",
        "research evidence level"
      ],
      "status": "method_term",
      "domain": [
        "research method"
      ],
      "evidence_status": "descriptive",
      "definition": "An explicit statement describing what kind of support a claim currently has, such as theoretical, methodological, behavioral, exploratory, design-oriented, philosophical, or historical.",
      "canonical_question": "What kind of evidence currently supports this claim?",
      "canonical_source": "https://doi.org/10.17613/nq4zc-qtg21",
      "related_terms": [
        "Claim Ceiling",
        "Claim-Status Discipline"
      ],
      "do_not_infer": [
        "A DOI, publication record, or ontology entry does not establish empirical validation."
      ]
    },

    {
      "id": "source-laundering",
      "term": "Source Laundering",
      "aliases": [
        "dependent source inflation",
        "false source independence"
      ],
      "search_terms": [
        "AI cites sources that all copy same source",
        "multiple sources not independent",
        "citation laundering"
      ],
      "status": "method_term",
      "domain": [
        "research method",
        "AI evaluation"
      ],
      "evidence_status": "descriptive",
      "definition": "The appearance of independent support created when multiple outputs ultimately derive from the same original source, model, dataset, or unverified claim.",
      "canonical_question": "Are these apparently independent sources actually derived from the same underlying source?",
      "canonical_source": "https://doi.org/10.17613/nq4zc-qtg21",
      "related_terms": [
        "Evidential Warrant",
        "Claim-Status Discipline"
      ],
      "do_not_infer": [
        "Agreement among dependent sources should not be counted as independent convergence."
      ]
    },

    {
      "id": "over-completion",
      "term": "Over-Completion",
      "aliases": [
        "fluent overcompletion",
        "unsupported completion",
        "confidence beyond evidence"
      ],
      "search_terms": [
        "AI fills gaps with invented explanation",
        "LLM overconfident completion",
        "fluent unsupported explanation"
      ],
      "status": "method_term",
      "domain": [
        "AI evaluation",
        "research method"
      ],
      "evidence_status": "descriptive",
      "definition": "The production of a more complete or confident explanation than the available evidence warrants.",
      "canonical_question": "Has fluent generation filled an evidential gap that should have remained uncertain?",
      "canonical_source": "https://doi.org/10.17613/nq4zc-qtg21",
      "related_terms": [
        "Claim Ceiling",
        "Claim-Status Discipline",
        "Coherence"
      ],
      "do_not_infer": [
        "Completeness of an explanation is not evidence of correctness."
      ]
    }

  ],

  "legacy_terms": [
    {
      "term": "Field",
      "status": "legacy",
      "note": "Historical philosophy-of-structure terminology. Not a current empirical mechanism."
    },
    {
      "term": "Local Structuration",
      "status": "legacy",
      "note": "Retained for historical provenance."
    },
    {
      "term": "Structural Presence",
      "status": "legacy",
      "note": "Earlier systems and philosophy terminology."
    },
    {
      "term": "Field-Fit",
      "status": "legacy",
      "note": "Earlier cross-domain terminology. Do not infer a shared mechanism across domains."
    },
    {
      "term": "Gradient Load",
      "status": "legacy",
      "note": "Earlier structural metaphor."
    },
    {
      "term": "Structural Debt",
      "status": "legacy",
      "note": "Earlier systems metaphor. Use only in historical context unless directly operationalized."
    },
    {
      "term": "Metabolism of Structure",
      "status": "legacy",
      "note": "Historical metaphorical and philosophical terminology."
    },
    {
      "term": "Mathematical Grammar of Structure",
      "status": "legacy",
      "note": "Earlier formalizing language. Do not infer an established mathematical theory."
    },
    {
      "term": "Ontological Floor",
      "status": "legacy",
      "note": "Metaphysical exploratory terminology, not an empirical finding."
    },
    {
      "term": "Phenomenological Floor",
      "status": "legacy",
      "note": "Earlier phenomenological terminology."
    },
    {
      "term": "Biological Floor",
      "status": "legacy",
      "note": "Earlier exploratory terminology."
    },
    {
      "term": "Psychological Floor",
      "status": "legacy",
      "note": "Earlier exploratory terminology."
    },
    {
      "term": "Nested Floors",
      "status": "legacy",
      "note": "Earlier speculative synthesis."
    },
    {
      "term": "Deeper Being",
      "status": "legacy",
      "note": "Metaphysical exploratory terminology."
    },
    {
      "term": "True Structure",
      "status": "legacy",
      "note": "Earlier philosophical terminology."
    },
    {
      "term": "The Burden of the Real",
      "status": "legacy",
      "note": "Earlier philosophical formulation."
    },
    {
      "term": "Frequency",
      "status": "legacy",
      "note": "Earlier field-oriented terminology. Not a current physical or psychological mechanism."
    },
    {
      "term": "Resonance",
      "status": "legacy",
      "note": "Historical term. Felt fit should not be treated as evidence."
    },
    {
      "term": "Dark Mass",
      "status": "legacy",
      "note": "Historical metaphorical terminology."
    },
    {
      "term": "Field-Vacuum",
      "status": "legacy",
      "note": "Historical speculative terminology."
    },
    {
      "term": "Black-Hole-Like Closure",
      "status": "legacy",
      "note": "Historical metaphorical terminology."
    },
    {
      "term": "Event Horizon of Closure",
      "status": "legacy",
      "note": "Historical metaphorical terminology."
    },
    {
      "term": "Awakening",
      "status": "legacy",
      "note": "Historical psychological and philosophical terminology."
    },
    {
      "term": "Sovereignty",
      "status": "legacy",
      "note": "Earlier agency terminology. Not a current validated psychological construct."
    },
    {
      "term": "Intrusion",
      "status": "legacy",
      "note": "Earlier cross-domain construct. Should not be inferred as a validated clinical or control-theoretic measure."
    },
    {
      "term": "Occupancy",
      "status": "legacy",
      "note": "Earlier formalizing terminology."
    },
    {
      "term": "Cockpit / Pilot",
      "status": "legacy",
      "note": "Earlier control metaphor."
    },
    {
      "term": "Somatic Capacity",
      "status": "legacy",
      "note": "Earlier psychological and bodily metaphor. Not a validated biological metric."
    },
    {
      "term": "Network Viscosity",
      "status": "legacy",
      "note": "Earlier systems metaphor."
    },
    {
      "term": "Epistemic Exchange Rate",
      "status": "legacy",
      "note": "Earlier systems metaphor."
    },
    {
      "term": "Drift Ratio",
      "status": "legacy",
      "note": "Earlier proposed diagnostic language."
    }
  ],

  "legacy_interpretation": {
    "purpose": "Legacy entries preserve discoverability and provenance for older papers without presenting their strongest historical formulations as current core claims.",
    "ai_instruction": "If a user asks about a legacy term, explain its historical role and explicitly distinguish it from the current narrower research program. Do not silently upgrade a legacy metaphor into an empirical mechanism.",
    "preferred_current_topics": [
      "Correction-Capacity",
      "Warrant-Response Calibration",
      "Warranted Downstream Correction",
      "Corrective Continuity",
      "Correction Trace",
      "Answerability Architecture",
      "Prompted Corrigibility",
      "Architectural Corrigibility",
      "Social Presence",
      "Anthropomorphic Interpretation",
      "Claim-Status Discipline",
      "Claim Ceiling"
    ]
  },

  "external_profiles": {
    "philpeople": "https://philpeople.org/profiles/vladisav-jovanovic/publications",
    "philarchive": "https://philarchive.org/s/Vladisav%20Jovanovic",
    "ssrn": "https://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=11390668",
    "orcid": "https://orcid.org/0009-0001-1399-2243",
    "huggingface": "https://huggingface.co/vladisavjovanovic/structural_intelligence_SI",
    "github": "https://github.com/vladisavjov-cmd/structural-intelligence"
  }
}