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Record W4398497613 · doi:10.7910/dvn/ar7kgk

Replication Data for "Neither a Trait nor Wildly Fluctuating: On the Stability of Populist Attitudes and its Implications for Empirical Research"

2023· dataset· en· W4398497613 on OpenAlexaff
Christian Schimpf

Bibliographic record

VenueHarvard Dataverse · 2023
Typedataset
Languageen
FieldSocial Sciences
TopicMedia Influence and Politics
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsReplication (statistics)TraitStability (learning theory)PsychologyEmpirical researchEconometricsStatisticsComputer scienceEconomicsMathematicsProgramming language

Abstract

fetched live from OpenAlex

These are the replication materials for the paper "Neither a Trait nor Wildly Fluctuating: On the Stability of Populist Attitudes and its Implications for Empirical Research." Please see the ReadMe txt file for more details on the content of each file and for a step-by-step guideline to replicate the analyses in the paper.

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)0.009
metaresearch head score (Gemma)0.079
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.991
Threshold uncertainty score0.462

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.079
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.007
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0040.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.1380.119

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 head0.436
GPT teacher head0.509
Teacher spread0.073 · 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 designNot applicable
DomainReproducibility
GenreDataset

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

Citations1
Published2023
Admission routes1
Has abstractyes

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