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Record W2725346411 · doi:10.1111/boer.12114

WHAT DETERMINES VACATION LEAVE? THE ROLE OF GENDER

2017· article· en· W2725346411 on OpenAlex
Ali Fakih

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBulletin of Economic Research · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Promotion (chess)Set (abstract data type)Working timeWorking hoursDemographic economicsBusinessMarketingLabour economicsEconomicsComputer sciencePolitical scienceEngineering

Abstract

fetched live from OpenAlex

ABSTRACT Vacation leave is introduced in workplaces to improve the working environment. Surprisingly, it has been observed that a large number of workers do not use all of their entitled vacation days. This paper provides a novel set of facts about the gender differences in taking vacation time using the Canadian Workplace Employee Survey, which is a linked longitudinal employer‐employee dataset. The results show considerable differences between men and women in the estimated effects of some demographic characteristics after controlling for job and workplace characteristics. However, they reveal significant implications of work arrangements (e.g., part‐time work, flexible work schedules, and home‐based work), job promotion, supervisory tasks, and union membership for vacation use, for both men and women. This paper provides further insights on the use of fringe benefits that may be useful to policymakers and businesses.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score1.000

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.154
GPT teacher head0.420
Teacher spread0.266 · 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