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Record W4393356929 · doi:10.1080/13639080.2024.2335464

The effect of fields of study on the waiting time to employment: evidence from the National Graduate Survey of Canada 2005 and 2009/10 cohorts

2024· article· en· W4393356929 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Education and Work · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor market dynamics and wage inequality
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedical educationPsychologySociologyDemographic economicsPublic relationsPolitical scienceMedicineEconomics

Abstract

fetched live from OpenAlex

By utilising the National Graduate Survey (NGS) – class of 2005 and 2009/10 – this paper examines the effects of fields of study on the time it takes to find full-time employment that lasts at least six months among graduates of Canadian Universities. Within cohorts, the results suggest considerable differences in the duration to first job after graduation for various fields of study – with ‘Agriculture, natural resources and conservation’, ‘Health and related fields’, and STEM fields like Math, Computer Science, and Engineering landing jobs the quickest, respectively. In contrast, the graduates of ‘Humanities’ and ‘Education’ had the longest duration of finding employment. The results also show large differences between cohorts, with the 2009/10 cohort taking much longer to find employment. Lastly, this paper did not find clear evidence that the effects of fields of study on the duration to exiting unemployment changed across the cohorts.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 head0.050
GPT teacher head0.288
Teacher spread0.238 · 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