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Record W2962852283 · doi:10.1556/032.2019.69.2.5

Self-Identification of Polish Academic Economists with Schools of Economic Thought*

2019· article· en· W2962852283 on OpenAlexaboutno aff
Grzegorz Konat, Wanda Karpińska-Mizielińska, Kazimierz Kloc, Tadeusz Smuga, Bartosz Witkowski

Bibliographic record

VenueActa Oeconomica · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsnot available
Fundersnot available
KeywordsOrthodoxyIdentification (biology)Quarter (Canadian coin)Economic ThoughtAssociation (psychology)Schools of economic thoughtEconomicsPositive economicsSociologyPolitical sciencePsychologyNeoclassical economicsGeography

Abstract

fetched live from OpenAlex

The paper presents the results of a research conducted in 2014–2016, aimed at characterising the milieu of the Polish academic economists with respect to their self-identification with modern schools of economic thought. Using econometric modelling, the social variables determining the theoretical choices made by the economists themselves were identified. We found that the largest group of the Polish academic economists identifies themselves with new institutional economics. Nearly half of the respondents declared their association with heterodox approaches, while only about a quarter of the respondents showed association with economic orthodoxy. Such a structure of self-identification of the Polish academic economists with schools of economic thought distinguishes it from the ones in other European countries, such as Italy and Germany.

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)0.008
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.004
Science and technology studies0.0020.003
Scholarly communication0.0050.002
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.220
Teacher spread0.207 · 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.

Study designObservational
DomainEvaluation
GenreEmpirical

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

Citations3
Published2019
Admission routes1
Has abstractyes

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