{ "model": { "rank": 4426, "code": "thing-q160039", "model_id": "vr.tr.econometrics", "name": "econometrics", "purpose": "Enable an agent to recognise econometrics as a field, assess the evidential requirements of its methods and applications, and decide which analyses or claims require further justification.", "family": "Thing Registry", "category": "Information and virtual systems", "status": "research-draft", "kind": "thing", "plane": "INF", "domain": "INF.KNW", "industry": "", "version": "", "url": "/models/thing/q160039/", "tier": 2, "score": 75, "payload": { "layer": "wikidata", "aliases": [ "Bayesian econometrics", "spatial econometrics" ], "aliasCount": 2, "merged": 2, "knownIn": 75, "facets": null, "markers": [], "lexicalClass": "", "senseRank": null, "alsoRegisteredAs": null, "source": { "dataset": "wikidata", "item": "Q160039", "url": "https://www.wikidata.org/wiki/Q160039", "license": "CC0 1.0" } }, "research": { "vercy": "1.0-draft", "publication": { "status": "research-draft", "adjudicationStatus": "unreviewed", "publishableCanonical": false, "generatedAt": "2026-09-09T20:11:29Z", "providers": [ "Codex" ], "breadth": "recalled by Codex without web access - no source was read", "missingProviders": [], "pass": 2, "cost": { "grok": { "seconds": 20.6, "error": "Reading additional input from stdin...\nOpenAI Codex v0.153.4\n--------\nworkdir: R:\\02_PROJECTS\\02_Meta_Models_Platforms\\Ver.cy\\current\\thing-registry-backlog\nmodel: gpt-6-astra\nprovider: openai\napproval: never\nsandbox: read-only\nreasoning effort: none\nreasoning summaries: none\nsession id: 01a087cb-1689-7bf3-b2fd-5adf11dbafde\n--------\nuser\nDescribe what is already known about one registered thing. Answer as JSON only, no prose around it.\n\nThing: econometrics\nSense to describe: (none recorded)\nDomain code: INF.KNW\nAlso known as: (none)\n\n\nContext for this batch of 695 things:\n# Batch 004: 1001 reg", "usd": 0, "recall": true }, "codex": { "seconds": 61.4, "error": "Reading additional input from stdin...\nOpenAI Codex v0.153.4\n--------\nworkdir: R:\\02_PROJECTS\\02_Meta_Models_Platforms\\Ver.cy\\current\\thing-registry-backlog\nmodel: gpt-6-astra\nprovider: openai\napproval: never\nsandbox: read-only\nreasoning effort: none\nreasoning summaries: none\nsession id: 01a087cb-167e-7f90-8e89-3c055682939a\n--------\nuser\nYou are drafting a Vercy meta-model for one registered thing. Answer as JSON only, no prose around it.\n\nThing: econometrics\nRegistry id: vr.tr.econometrics\nPlane / domain: INF / INF.KNW\nRegistry definition: (none recorded)\nNames folded into this entry: (none)\n" } } }, "metaModel": { "id": "THING-Q160039", "registryId": "vr.tr.econometrics", "name": "econometrics", "version": "0.1.0-research.1", "entryKind": "thing", "family": "Thing Registry", "domain": [ "INF.KNW" ], "status": "research-draft" }, "canonicalUrl": "https://ver.cy/models/thing/q160039/", "model": { "registry_id": "vr.tr.econometrics", "name": "econometrics", "purpose": "Enable an agent to recognise econometrics as a field, assess the evidential requirements of its methods and applications, and decide which analyses or claims require further justification.", "definition": "Econometrics is the field that combines economic theory, probability and statistical methods to estimate economic relationships, test hypotheses and predict outcomes from data under explicit assumptions.", "scope_statement": "This model owns econometrics as a discipline concerned with using statistical and mathematical methods to connect economic questions, models and observed data through identification, estimation, testing and prediction; individual studies, datasets, software and practitioners remain related entities.", "in_scope": [ "Economic subject matter and the relationship between economic models and empirical evidence", "Identification, estimation, inference and prediction as distinct methodological tasks", "Economic data structures, measurement problems and observation processes", "Standards for assessing econometric assumptions, uncertainty and empirical credibility", "Subfields, disciplinary boundaries, institutional markers and classification conventions" ], "out_of_scope": [ "Economic theory that makes no substantive connection to statistical evidence", "General statistical methods considered independently of economic applications or econometric development", "Individual datasets, their storage infrastructure and access administration", "Individual research projects, publications and policy decisions as managed objects", "Econometricians, departments, professional societies and journals as people or organisations", "Software packages and computing infrastructure as engineered products" ], "distinguishing_features": [ "An economic application connects an economic question or model to observed data and makes the statistical basis of estimation, testing or prediction explicit.", "Theoretical econometrics develops or evaluates methods for econometric problems; it need not analyse a particular economic dataset.", "Compared with mathematical economics alone, econometrics addresses the relationship between a model and observations, including sampling variation or other statistical uncertainty.", "Compared with descriptive economic statistics alone, econometric work specifies a model or inferential framework for learning relationships, testing restrictions or predicting outcomes.", "Neither regression use nor causal language alone establishes that work is econometrics; classification also requires its economic purpose or relationship to the field's methodological literature." ], "characteristics": [ { "name": "Empirical objective", "kind": "category", "unit_or_values": "Description; estimation; hypothesis testing; causal inference; prediction; structural counterfactual analysis; multiple objectives", "why_it_matters": "Different objectives require different assumptions, diagnostics and standards of success." }, { "name": "Relationship to economic theory", "kind": "category", "unit_or_values": "Theory-imposed restrictions; theory-informed specification; primarily predictive; methodological development; mixed or contested", "why_it_matters": "Shows how economic reasoning enters the analysis and which conclusions depend on it." }, { "name": "Identification status", "kind": "state", "unit_or_values": "Not assessed; point identified; partially identified; not identified; conditional on disputed assumptions", "why_it_matters": "Separates what the assumed population model can establish from what an estimator can compute." }, { "name": "Observation structure", "kind": "category", "unit_or_values": "Cross-section; time series; panel; repeated cross-sections; spatial or network data; mixed structures", "why_it_matters": "Dependence, heterogeneity and sampling structure affect appropriate methods and uncertainty estimates." }, { "name": "Observation and assignment process", "kind": "category", "unit_or_values": "Experimental; observational; quasi-experimental design claim; simulated; mixed; undocumented", "why_it_matters": "Helps establish which selection and treatment-assignment assumptions need scrutiny." }, { "name": "Inferential framework", "kind": "category", "unit_or_values": "Frequentist; Bayesian; randomisation-based; other explicitly specified framework; mixed", "why_it_matters": "Determines how uncertainty statements should be interpreted and evaluated." }, { "name": "Methodological validation status", "kind": "state", "unit_or_values": "Unassessed; assumptions documented; diagnostics assessed; sensitivity assessed; replication assessed; limitations unresolved", "why_it_matters": "Supports a qualified assessment of evidence without treating a single diagnostic as proof of validity." }, { "name": "Disciplinary placement", "kind": "relation", "unit_or_values": "Links to named subfields, neighbouring disciplines and versioned classification schemes", "why_it_matters": "Makes conventional and overlapping field boundaries explicit." } ], "affordances": [ "Classify work as econometric, adjacent or boundary-contested using its purpose and methodological contribution.", "Map an economic question to its target quantity, data requirements and candidate methodological families.", "Separate identification assumptions from estimation choices and uncertainty calculations.", "Flag mismatches between an analysis's design and its causal, predictive or counterfactual claims.", "Request diagnostics, sensitivity analysis or replication evidence appropriate to the stated objective.", "Locate relevant subfields, literature and institutions through sourced disciplinary relationships." ] }, "sources": [], "structure": { "bundles": [ { "id": "economic-questions-and-field-boundaries", "name": "Economic questions and field boundaries", "description": "The economic purposes and methodological commitments that establish the field's scope.", "rationale": "An agent must recognise econometrics without equating it with every use of statistics in economics or limiting it to applied regression.", "layers": [ { "id": "economic-targets", "name": "Economic targets", "description": "How economic questions become quantities, hypotheses or predictions that data can address.", "findings": [ { "id": "question-to-target", "name": "Question-to-target connection", "description": "Record whether work targets an economic relationship, causal effect, forecast, model restriction or methodological property.", "questions": [ { "text": "Which economic question or recurring econometric problem motivates the work?", "kind": "definition", "id": "question-to-target-q01" }, { "text": "What quantity, hypothesis or prediction would count as answering that question?", "kind": "measurement", "id": "question-to-target-q02" } ] } ] }, { "id": "neighbouring-disciplines", "name": "Neighbouring disciplines", "description": "Boundaries with statistics, mathematical economics, economic measurement and machine learning.", "findings": [ { "id": "disciplinary-membership", "name": "Basis of disciplinary membership", "description": "Record the convention under which an application or theoretical contribution belongs to econometrics, including legitimate overlap.", "questions": [ { "text": "What connects this work to econometrics beyond its use of a statistical technique?", "kind": "boundary", "id": "disciplinary-membership-q01" }, { "text": "Which disciplinary source supports this placement, and does it recognise overlapping membership?", "kind": "provenance", "id": "disciplinary-membership-q02" } ] } ] } ] }, { "id": "economic-data-and-measurement", "name": "Economic data and measurement", "description": "The observation structures and measurement choices on which econometric reasoning depends.", "rationale": "Economic variables are operationalised through observation processes that can change the meaning and credibility of estimated relationships.", "layers": [ { "id": "constructs-and-observations", "name": "Constructs and observations", "description": "Connections between economic concepts and recorded variables.", "findings": [ { "id": "economic-variable-operationalisation", "name": "Economic variable operationalisation", "description": "Record how concepts such as income, prices, productivity or expectations are represented, transformed and compared.", "questions": [ { "text": "How is each target economic construct represented, including units, aggregation, deflation or proxy choices?", "kind": "measurement", "id": "economic-variable-operationalisation-q01" }, { "text": "Which measurement errors, revisions or definition changes could alter the interpretation of the relationship?", "kind": "boundary", "id": "economic-variable-operationalisation-q02" } ] } ] }, { "id": "sampling-time-and-dependence", "name": "Sampling, time and dependence", "description": "How units enter the data and how observations relate across time, groups or locations.", "findings": [ { "id": "observation-process", "name": "Observation process", "description": "Record sampling, selection, attrition, timing and dependence features that constrain econometric methods.", "questions": [ { "text": "How were units selected and observed, and which population and period can they represent?", "kind": "provenance", "id": "observation-process-q01" }, { "text": "Which serial, clustered, spatial or cross-sectional dependencies must the analysis accommodate?", "kind": "measurement", "id": "observation-process-q02" } ] } ] } ] }, { "id": "identification-and-economic-interpretation", "name": "Identification and economic interpretation", "description": "Conditions under which observed evidence can determine the economic objects an analysis claims to recover.", "rationale": "Computing a coefficient does not establish that it answers the economic question or supports the proposed intervention.", "layers": [ { "id": "targets-and-identifying-restrictions", "name": "Targets and identifying restrictions", "description": "The link between target quantities, observable distributions and maintained assumptions.", "findings": [ { "id": "identification-argument", "name": "Identification argument", "description": "Record whether the target is uniquely recoverable, bounded or unidentified under the stated model and assumptions.", "questions": [ { "text": "Which assumptions connect the target quantity to the observable distribution?", "kind": "definition", "id": "identification-argument-q01" }, { "text": "Do those assumptions imply point identification, partial identification or non-identification?", "kind": "boundary", "id": "identification-argument-q02" } ] } ] }, { "id": "causality-and-counterfactuals", "name": "Causality and counterfactuals", "description": "Additional requirements for interpreting relationships as intervention effects or policy counterfactuals.", "findings": [ { "id": "intervention-claim-warrant", "name": "Intervention claim warrant", "description": "Record assignment, exclusion, comparability or structural assumptions and the populations or regimes over which conclusions are claimed.", "questions": [ { "text": "How does the design address confounding, simultaneity, selection or other relevant sources of endogeneity?", "kind": "boundary", "id": "intervention-claim-warrant-q01" }, { "text": "What additional assumptions are needed to use the result for a new population, policy or equilibrium?", "kind": "action", "id": "intervention-claim-warrant-q02" } ] } ] } ] }, { "id": "estimation-inference-and-performance", "name": "Estimation, inference and performance", "description": "How econometric procedures produce results and how those results are evaluated.", "rationale": "An agent must distinguish estimator properties, uncertainty claims and predictive performance when judging an analysis.", "layers": [ { "id": "estimation-and-uncertainty", "name": "Estimation and uncertainty", "description": "The fit between procedures, data conditions and the interpretation of uncertainty.", "findings": [ { "id": "procedure-validity", "name": "Procedure validity", "description": "Record the conditions supporting estimation and inference, including finite-sample limitations and relevant asymptotic arguments.", "questions": [ { "text": "Which properties justify the estimator for this target and data structure, and under what conditions?", "kind": "definition", "id": "procedure-validity-q01" }, { "text": "How are uncertainty estimates affected by dependence, weak identification, model selection or limited sample size?", "kind": "measurement", "id": "procedure-validity-q02" } ] } ] }, { "id": "diagnostics-and-validation", "name": "Diagnostics and validation", "description": "Evidence that tests an analysis against plausible failures and its stated objective.", "findings": [ { "id": "objective-specific-validation", "name": "Objective-specific validation", "description": "Record specification checks, sensitivity analyses, forecast evaluation and reproducibility evidence without treating them as interchangeable guarantees.", "questions": [ { "text": "Which diagnostics or sensitivity analyses address the assumptions most consequential for the stated conclusion?", "kind": "action", "id": "objective-specific-validation-q01" }, { "text": "For predictive work, how are performance and uncertainty evaluated on appropriately separated observations without future-information leakage?", "kind": "measurement", "id": "objective-specific-validation-q02" }, { "text": "Can the reported results be reproduced from the documented data transformations and computational procedure?", "kind": "provenance", "id": "objective-specific-validation-q03" } ] } ] } ] }, { "id": "disciplinary-organisation-and-sources", "name": "Disciplinary organisation and sources", "description": "The classifications, institutions and reference works through which econometrics is organised.", "rationale": "Field recognition needs sourced conventions and intellectual context while keeping organisations and publications as linked entities.", "layers": [ { "id": "subfields-and-classifications", "name": "Subfields and classifications", "description": "Placement of econometrics and its internal specialisations in named classification systems.", "findings": [ { "id": "versioned-field-placement", "name": "Versioned field placement", "description": "Record verified labels and codes, their scheme versions and the distinctions each scheme makes.", "questions": [ { "text": "Which verified entries in JEL, MSC, UDC, DDC or other relevant schemes cover econometrics, and in which editions?", "kind": "provenance", "id": "versioned-field-placement-q01" }, { "text": "How does each scheme distinguish econometric theory, applied econometrics and neighbouring statistical or economic fields?", "kind": "boundary", "id": "versioned-field-placement-q02" } ] } ] }, { "id": "institutions-and-reference-literature", "name": "Institutions and reference literature", "description": "Evidence of disciplinary recognition and sources that articulate methods and boundaries.", "findings": [ { "id": "institutional-and-literature-markers", "name": "Institutional and literature markers", "description": "Link learned societies, journal scopes, degree curricula and defining handbooks to the specific aspects of econometrics they document.", "questions": [ { "text": "Which society statements, journal scopes and degree curricula explicitly identify econometrics as a field or specialisation?", "kind": "provenance", "id": "institutional-and-literature-markers-q01" }, { "text": "Which handbooks or methodological reviews support the proposed coverage, and where do their definitions differ?", "kind": "boundary", "id": "institutional-and-literature-markers-q02" } ] } ] } ] }, { "id": "evidence-and-external-alignment", "name": "Evidence and external alignment", "description": "What the world already says about this thing, gathered so the model can be checked against it.", "rationale": "A model that cannot be lined up against existing standards, identifiers and practice cannot be adopted by anyone who already uses them.", "layers": [ { "id": "reported-evidence", "name": "Reported evidence", "description": "Findings from the breadth pass, kept separate from the structural claims.", "findings": [ { "id": "evidence-confidence-notes", "name": "Check these first", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ "This describes the academic discipline, rather than its practitioners or literature; no narrower registry sense was supplied.", "The Econometric Society and its journal Econometrica are established institutional markers; the listed kinds overlap rather than forming an exclusive classification.", "No sources were consulted; classification details should be verified before publication, and the field has no single intrinsic measurement scale or universal technical standard." ], "questions": [ { "id": "evidence-confidence-notes-q01", "text": "Which of these check these first hold for the sense of econometrics this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-kinds", "name": "Kinds and varieties", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ "Theoretical econometrics", "Applied econometrics", "Microeconometrics", "Macroeconometrics", "Time-series econometrics", "Panel-data econometrics" ], "questions": [ { "id": "evidence-kinds-q01", "text": "Which of these kinds and varieties hold for the sense of econometrics this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-identifiers", "name": "Identifiers and schemes", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ { "scheme": "JEL Classification System", "value_or_pattern": "C01", "note": "Econometrics; maintained by the American Economic Association within category C, Mathematical and Quantitative Methods." } ], "questions": [ { "id": "evidence-identifiers-q01", "text": "Which of these identifiers and schemes hold for the sense of econometrics this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-real-world-use", "name": "Real-world use", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ "Estimating effects of policies or interventions when the research design supports causal identification", "Forecasting economic quantities such as inflation, employment and output", "Estimating consumer demand, price elasticities and firm behaviour", "Testing economic theories against observed data", "Estimating and evaluating models of financial returns and risk" ], "questions": [ { "id": "evidence-real-world-use-q01", "text": "Which of these real-world use hold for the sense of econometrics this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-failure-modes-and-hazards", "name": "Failure modes and hazards", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ "Endogeneity, including omitted confounding, simultaneity and some forms of measurement error, can invalidate coefficient interpretations.", "Weak instruments or failure of identifying assumptions can make causal estimates unreliable.", "Ignoring nonstationarity, serial dependence or structural breaks can produce misleading time-series results.", "Incorrect treatment of heteroskedasticity, clustering or sample selection can invalidate inference.", "Specification searching, multiple testing and selective reporting can exaggerate evidence." ], "questions": [ { "id": "evidence-failure-modes-and-hazards-q01", "text": "Which of these failure modes and hazards hold for the sense of econometrics this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-neighbours", "name": "Neighbouring kinds and how to tell them apart", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ { "name": "Statistics", "difference": "Statistics develops methods for learning from data generally; econometrics adapts and develops these methods around economic questions, models and identification problems." }, { "name": "Mathematical economics", "difference": "Mathematical economics formalises economic reasoning; econometrics connects models and hypotheses to observed data through estimation and inference." }, { "name": "Economic statistics", "difference": "Economic statistics emphasises constructing and describing economic data and indicators; econometrics emphasises estimating relationships and testing models using such data." }, { "name": "Causal inference", "difference": "Causal inference studies intervention effects across disciplines; econometrics overlaps substantially but also includes forecasting and estimation without causal claims." }, { "name": "Machine learning", "difference": "Machine learning often emphasises predictive performance and flexible algorithms; econometrics also emphasises economic interpretation, identification and statistical inference, with substantial methodological overlap." } ], "questions": [ { "id": "evidence-neighbours-q01", "text": "Which of these neighbouring kinds and how to tell them apart hold for the sense of econometrics this model covers, and on what evidence?", "kind": "provenance" } ] } ] } ] } ] }, "openQuestions": [ "Does an existing Vercy world model already cover econometrics, requiring this registry entry to link to that publication?", "Which authoritative definitions best support the boundary between econometrics, economic statistics, statistics and machine learning?", "What are the exact econometrics entries and scope notes in the relevant editions of JEL, MSC, UDC and DDC?", "Which subfields require explicit treatment beyond the proposed structure, particularly structural econometrics, financial econometrics, Bayesian econometrics and econometric machine learning?", "Which institutional sources and defining handbooks provide sufficiently broad coverage without making one methodological tradition stand for the entire field?" ], "statistics": { "bundles": 6, "layers": 11, "findings": 16, "questions": 27 } }, "draft": { "generator": "vr.draft.v3", "status": "draft-generated", "researched": false, "archetype": "discipline or field of knowledge", "method": "Written from the archetype playbook - what this kind of thing needs beyond identity and provenance - and from the structure that recurred across 6,333 models already researched by two engines. Applied to this entry by rule. No source was read for this thing and no claim here is researched. This entry carries no facets of its own, so they were inferred from its domain - a guess about a whole domain applied to one thing.", "facetsInferred": true, "nextPass": "A researcher replaces this draft with a sourced specification. Treat every sentence below as a proposal to argue with.", "purpose": "Give an agent a durable, checkable way to recognise a econometrics, record what state it is in, and decide what may be done with it.", "whatItIs": "Enable an agent to recognise econometrics as a field, assess the evidential requirements of its methods and applications, and decide which analyses or claims require further justification.", "characteristics": { "substance": "information", "origin": "conceptual", "agency": "inert" }, "whatYouCanDoWithIt": [ "read and interpreted" ], "distinguishingFeatures": [ "Names folded into this entry, which a task may need to split apart again: Bayesian econometrics, spatial econometrics.", "2 finer distinctions are held as aliases rather than separate entries, because telling them apart needs a task that asks for it.", "Described in 75 Wikipedia languages, which is a measure of how widely the thing is known, not of how important it is." ], "openQuestionsForResearch": [ "Which of the bundles below does a real task actually need, and which are ceremony?", "What does this thing have that the facets do not capture at all?", "Which neighbouring kind is most often confused with a econometrics, and on what evidence are they told apart?" ], "whatItIsMadeOf": "content that has to be carried by something else", "physicalCharacter": [ "Does nothing on its own; everything it does, something else did to it.", "These come from the domain this entry sits in rather than from the entry itself, so treat them as a first guess about the whole domain applied to one thing." ], "whatCanBeDoneWithIt": [ "read it and act on what it says" ], "howItIsRecognised": [], "relatedModels": [ { "relation": "covers", "note": "Finer kinds folded into this entry because telling them apart needs a task that asks for it. Each is a model waiting to be split out when one does.", "targets": [ "Bayesian econometrics", "spatial econometrics" ] } ], "standing": "Described in 75 Wikipedia languages, which measures how widely it is written about rather than how important or how common it is. 2 finer distinctions are held inside this entry as names rather than as separate models.", "structure": { "bundles": [ { "id": "identity-and-classification", "name": "Identity, naming and classification", "description": "How an agent tells one econometrics from another, and a econometrics from things that resemble it.", "rationale": "Recognition comes before every other claim. Without stable identity nothing else in the model can be trusted to be about the same thing twice.", "layers": [ { "id": "naming-and-identifiers", "name": "Names and identifiers", "description": "The names this thing goes by and the identifiers that survive translation and time.", "findings": [ { "id": "preferred-name-and-aliases", "name": "Preferred name, aliases and local names", "description": "Which name to use, which names mean the same thing, and which merely sound similar.", "questions": [ { "id": "preferred-name-and-aliases-q01", "text": "What identifies and describes the name of a econometrics, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "preferred-name-and-aliases-q02", "text": "Who or what asserted this about the name of a econometrics, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "preferred-name-and-aliases-q03", "text": "What may an agent decide or do once the name of a econometrics is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] }, { "id": "stable-identifiers", "name": "Stable identifiers and external keys", "description": "Identifiers that keep pointing at this kind of thing across systems and languages.", "questions": [ { "id": "stable-identifiers-q01", "text": "What identifies and describes an identifier for a econometrics, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "stable-identifiers-q02", "text": "Who or what asserted this about an identifier for a econometrics, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "stable-identifiers-q03", "text": "What may an agent decide or do once an identifier for a econometrics is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] }, { "id": "classification-and-granularity", "name": "Classification and granularity", "description": "Where a econometrics sits among kinds, and how finely a task needs to cut it.", "findings": [ { "id": "kind-and-parents", "name": "Kind, parents and neighbouring kinds", "description": "The classes this thing belongs to and the ones it is next to.", "questions": [ { "id": "kind-and-parents-q01", "text": "What identifies and describes the kind of a econometrics, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "kind-and-parents-q02", "text": "Who or what asserted this about the kind of a econometrics, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "kind-and-parents-q03", "text": "What may an agent decide or do once the kind of a econometrics is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] }, { "id": "distinguishing-features", "name": "Distinguishing features", "description": "What separates a econometrics from the things most often confused with it.", "questions": [ { "id": "distinguishing-features-q01", "text": "What identifies and describes what distinguishes a econometrics, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "distinguishing-features-q02", "text": "Who or what asserted this about what distinguishes a econometrics, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "distinguishing-features-q03", "text": "What may an agent decide or do once what distinguishes a econometrics is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] } ] }, { "id": "state-and-lifecycle", "name": "State and lifecycle", "description": "The states a econometrics passes through and the events that move it between them.", "rationale": "Most decisions about a thing depend on what state it is in now, which is a claim with a time on it, not a property.", "layers": [ { "id": "lifecycle-stages", "name": "Lifecycle stages", "description": "From coming into existence to ceasing to be one of these.", "findings": [ { "id": "stages-and-transitions", "name": "Stages and transitions", "description": "The stages worth naming and what moves a econometrics between them.", "questions": [ { "id": "stages-and-transitions-q01", "text": "What identifies and describes the lifecycle of a econometrics, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "stages-and-transitions-q02", "text": "Who or what asserted this about the lifecycle of a econometrics, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "stages-and-transitions-q03", "text": "What may an agent decide or do once the lifecycle of a econometrics is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] }, { "id": "observations-and-status", "name": "Observations and current status", "description": "What is observed about a econometrics, how often and by whom.", "findings": [ { "id": "observation-record", "name": "Observation record", "description": "How an observation of a econometrics is recorded so that it can be superseded rather than overwritten.", "questions": [ { "id": "observation-record-q01", "text": "What identifies and describes an observation of a econometrics, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "observation-record-q02", "text": "Who or what asserted this about an observation of a econometrics, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "observation-record-q03", "text": "What may an agent decide or do once an observation of a econometrics is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] } ] }, { "id": "content-and-access", "name": "Content, encoding and access", "description": "What a econometrics says, how it is encoded and who may read it.", "rationale": "An informational thing carries content that can be copied, versioned and withheld, none of which its physical carrier explains.", "layers": [ { "id": "content-and-encoding", "name": "Content and encoding", "description": "The content itself, its format and its language.", "findings": [ { "id": "content-and-format", "name": "Content, format and language", "description": "What a econometrics contains and in what form it is held.", "questions": [ { "id": "content-and-format-q01", "text": "What identifies and describes the content of a econometrics, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "content-and-format-q02", "text": "Who or what asserted this about the content of a econometrics, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "content-and-format-q03", "text": "What may an agent decide or do once the content of a econometrics is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] }, { "id": "access-and-rights", "name": "Access, rights and retention", "description": "Who may read, copy or change it, and for how long it is kept.", "findings": [ { "id": "access-rules", "name": "Access rules and retention", "description": "The permissions attached to a econometrics and the period it survives.", "questions": [ { "id": "access-rules-q01", "text": "What identifies and describes access to a econometrics, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "access-rules-q02", "text": "Who or what asserted this about access to a econometrics, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "access-rules-q03", "text": "What may an agent decide or do once access to a econometrics is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] } ] }, { "id": "subject-and-method", "name": "Subject matter and method", "description": "What econometrics studies and how it establishes anything.", "rationale": "A field is identified by its questions and its methods, and those are what distinguish it from the fields next to it.", "layers": [ { "id": "subject", "name": "Subject matter", "description": "The questions it takes as its own.", "findings": [ { "id": "subject-record", "name": "Questions and objects of study", "description": "What it is about, stated so a neighbouring field can be told apart.", "questions": [ { "id": "subject-record-q01", "text": "What questions and objects does econometrics take as its own?", "kind": "definition" }, { "id": "subject-record-q02", "text": "Which questions does it share with a neighbouring field, and who claims them?", "kind": "boundary" } ] } ] }, { "id": "method", "name": "Method and evidence", "description": "How claims are established and what counts as evidence.", "findings": [ { "id": "method-record", "name": "Methods and standards of evidence", "description": "The methods used and what they are taken to establish.", "questions": [ { "id": "method-record-q01", "text": "By what methods does econometrics establish claims, and what counts as sufficient evidence?", "kind": "provenance" }, { "id": "method-record-q02", "text": "What kind of claim can this field not settle, and where should an agent look instead?", "kind": "action" } ] } ] } ] }, { "id": "institutions-and-classification", "name": "Institutions and classification", "description": "Where econometrics is practised and how catalogues place it.", "rationale": "The institutional footprint is the evidence that a field exists as a field rather than as a topic.", "layers": [ { "id": "institutions", "name": "Institutional markers", "description": "Societies, journals, degrees and departments.", "findings": [ { "id": "institution-record", "name": "Bodies and venues", "description": "Where the field organises itself.", "questions": [ { "id": "institution-record-q01", "text": "Which societies, journals or degrees mark econometrics as an established field?", "kind": "provenance" }, { "id": "institution-record-q02", "text": "What would show that it is emerging or dissolving rather than established?", "kind": "boundary" } ] } ] }, { "id": "classification", "name": "Classification schemes", "description": "Where library and research classifications put it.", "findings": [ { "id": "classification-record", "name": "Codes and their disagreements", "description": "The classification codes that place it, and where they differ.", "questions": [ { "id": "classification-record-q01", "text": "Which classification schemes place econometrics, under what codes?", "kind": "definition" }, { "id": "classification-record-q02", "text": "Where do those schemes disagree about its scope?", "kind": "boundary" } ] } ] } ] }, { "id": "provenance-and-evidence", "name": "Provenance, evidence and time", "description": "Where every claim about a econometrics came from and when it held.", "rationale": "A claim without a source and a time cannot be superseded, only overwritten, and an agent that overwrites loses the ability to explain itself.", "layers": [ { "id": "source-and-authority", "name": "Source and authority", "description": "Who said it, on what evidence, and how strongly.", "findings": [ { "id": "claim-provenance", "name": "Claim provenance and confidence", "description": "The authority behind each claim about a econometrics and how confident it is.", "questions": [ { "id": "claim-provenance-q01", "text": "What identifies and describes a claim about a econometrics, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "claim-provenance-q02", "text": "Who or what asserted this about a claim about a econometrics, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "claim-provenance-q03", "text": "What may an agent decide or do once a claim about a econometrics is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] }, { "id": "time-and-versions", "name": "Time, versions and supersession", "description": "When a claim was true, when it was learnt, and what replaced it.", "findings": [ { "id": "validity-and-supersession", "name": "Validity period and supersession", "description": "How an old claim about a econometrics is retired without being erased.", "questions": [ { "id": "validity-and-supersession-q01", "text": "What identifies and describes the validity of a claim about a econometrics, and in what units or vocabulary?", "kind": "definition", "answer_data": [ "identifiers", "types and classes", "values with units", "explicit unknowns" ] }, { "id": "validity-and-supersession-q02", "text": "Who or what asserted this about the validity of a claim about a econometrics, by which method, and when was it true?", "kind": "provenance", "answer_data": [ "authority", "method", "evidence", "event time", "knowledge time" ] }, { "id": "validity-and-supersession-q03", "text": "What may an agent decide or do once the validity of a claim about a econometrics is known, and what must it refuse?", "kind": "action", "answer_data": [ "permitted actions", "preconditions", "refusals", "escalation" ] } ] } ] } ] } ] }, "statistics": { "bundles": 6, "layers": 12, "findings": 14, "questions": 38 } } } }