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Replication Package for Why don’t Firms Hire Young Workers during Recessions? A Replication of Forsythe (2022)

2025· other· en· W6942969435 on OpenAlexaff

Bibliographic record

VenueZBW Journal Data Archive · 2025
Typeother
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Downsizing and Restructuring
Canadian institutionsQueen's UniversityBank of CanadaUniversity of Ottawa
Fundersnot available
KeywordsReplication (statistics)Key (lock)NegotiationContext (archaeology)

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.021
metaresearch head score (Gemma)0.187
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
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 score0.979
Threshold uncertainty score0.828

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.187
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0060.008
Science and technology studies0.0030.001
Scholarly communication0.0040.003
Open science0.0030.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.4190.181

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 head0.019
GPT teacher head0.265
Teacher spread0.247 · 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

Citations0
Published2025
Admission routes1
Has abstractno

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