MétaCan
Menu
Back to cohort
Record W3041916064 · doi:10.1111/kykl.12244

Shared Mental Models: Insights and Perspectives on Ideologies and Institutions

2020· article· en· W3041916064 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueKyklos · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsnot available
Fundersnot available
KeywordsOperationalizationIdeologyPoliticsCoronavirus disease 2019 (COVID-19)Game theoryQuarter (Canadian coin)PandemicMental healthPositive economicsSociologyEconomicsPolitical sciencePsychologyEpistemologyMicroeconomicsMedicineGeographyLaw

Abstract

fetched live from OpenAlex

SUMMARY This article leads off a special symposium comprised of a select group of public choice economists and political scientists that assembled to reflect on the important contribution that Arthur T. Denzau and Douglass C. North’s seminal piece on Shared Mental Models (1993) has made over the last quarter of a century. Relatedly, we apply concepts from Denzau and North’s Shared Mental Models to suggest a modified model of the Nash equilibrium used in non‐cooperative game theory to help us operationalize the “learning path” by which we can move from “siloed” thinking to a wider “systems” view of organizations, our environment, and indeed, the world. Our model has implications for the way we respond to economic crises, financial meltdowns, and global health epidemics, such as the COVID‐19 pandemic.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.136
GPT teacher head0.237
Teacher spread0.101 · 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