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Record W2072945613 · doi:10.1108/01443331011072280

Parental leave: from perception to first‐hand experience

2010· article· en· W2072945613 on OpenAlexaffabout
Diane‐Gabrielle Tremblay, Émilie Génin

Bibliographic record

VenueInternational Journal of Sociology and Social Policy · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsUniversité de MontréalUniversité TÉLUQUniversité du Québec à Montréal
Fundersnot available
KeywordsParental leaveOriginalityPerceptionValue (mathematics)PsychologyPublic policyVariance (accounting)Social psychologyDemographic economicsPolitical scienceBusinessWork (physics)EconomicsEngineering

Abstract

fetched live from OpenAlex

Purpose Paid parental leave for both mothers and fathers has fed countless debates. Four years after the implementation of a new parental leave policy in Quebec, this paper aims to assess how parental leave is perceived in the workplace. Design/methodology/approach Using data from employee surveys carried out in a municipal police service, the paper employs analysis of variance techniques to compare the perception of parental leave within two groups of respondents: those who had gone on parental leave and those who had not. Findings The findings highlight significant differences between the perceptions of parental leave entertained by the respondents who have taken it up and those who have not yet experienced parental leave. Social implications Analysing these differences has produced extremely interesting findings: adopting a public policy is not sufficient; organisations need to make employees feel supported in taking parental leave if they really want the policy to achieve the targeted results. Originality/value Paid parental leave is relatively new in Europe and almost non‐existent in North America and few studies have been carried out to measure their perception in the workplace. This research shows how important it is to follow the use of the policy to make sure that it does not have negative impacts for those who use it.

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 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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.718
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.027
GPT teacher head0.378
Teacher spread0.350 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations13
Published2010
Admission routes2
Has abstractyes

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Same venueInternational Journal of Sociology and Social PolicySame topicWork-Family Balance ChallengesFrench-language works237,207