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Record W2004942031 · doi:10.1080/13639080.2011.653554

Work intensity and non-completion of university: longitudinal approach and causal inference

2012· article· en· W2004942031 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Education and Work · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité du Québec à MontréalUniversité de Montréal
FundersUniversité de MontréalInstitut national de la recherche scientifique
KeywordsPsychologyCausal inferenceWork IntensityWork (physics)Social psychologyEconometricsEconomics

Abstract

fetched live from OpenAlex

Researchers focused upon the work–dropping out connection tend to show a U-shaped relationship between the likelihood of dropping out and the number of hours worked outside school, with a higher exit rate for both non-working students and for students whose working hours pass a critical threshold. Yet the data typically used by these researchers are drawn mainly from cross-sectional surveys, and as a result does not allow for any causal interpretation. The present article uses an event history analysis of Canadian longitudinal data covering seven years of a cohort, and offers original findings on the causal work–dropping out relationship at the university level. We find evidence showing that the evolution of the exit rates and the factors influencing the decision to quit a particular university programme differ substantially between students who want to enrol in another programme and those who do not. For the latter, we observe a critical threshold of 24 h of work, beyond which negative effects in terms of non-completion start to appear. We find no negative effects arising from not working vs. working a few hours. Our findings thus tend to show that the higher exit rate among non-working students evidenced in cross-sectional data should be attributed to the fact that academic difficulties cause some potential university dropouts to stop working and to devote more time to school.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.152

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.175
GPT teacher head0.393
Teacher spread0.217 · 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