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Economic Institutions and Institutional Change

2021· reference-entry· en· W4256138291 on OpenAlexaff
Kim Pernell

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsScholarshipEconomic sociologyStructuringInstitutional changeInstitutional economicsPolitical scienceSociologyPolitical economyEconomicsSocial scienceNeoclassical economicsEconomic growthPublic administrationLaw

Abstract

fetched live from OpenAlex

Interest in the institutions that structure economic behavior has a long history in sociology, extending back to the work of Marx, Weber, Durkheim, and Polanyi. With the rise of new economic sociology in the 1980s, scholars have direct renewed attention toward the informal and formal rules and conventions that structure economic life. Money, financial markets, complex organizations, and economic policies have received particular attention. One branch of scholarship in this area focuses on uncovering factors that drive the emergence or development of economic institutions. Another branch of scholarship examines the role of institutions in structuring economic behavior. A third line of research takes up the puzzle of institutional change: how stable economic conventions crumble and come to be replaced with new ones. The present article offers a broad survey of scholarship on economic institutions, with a particular focus on institutional variation and institutional change.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.005
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.019
Scholarly communication0.0050.005
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.118
GPT teacher head0.260
Teacher spread0.142 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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