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Record W4392745360 · doi:10.4000/osp.18799

Effets de facteurs induits par la pandémie de Covid-19 sur les caractéristiques d’un travail qui a du sens

2024· article· fr· W4392745360 on OpenAlexaffabout
Élodie Chevallier, Réginald Savard, Alexandre Brien, Pawel Zaniewski, Jean‐Luc Bernaud

Bibliographic record

VenueL’Orientation scolaire et professionnelle · 2024
Typearticle
Languagefr
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesCoronavirus disease 2019 (COVID-19)Political sciencePhilosophyMedicine

Abstract

fetched live from OpenAlex

Cette recherche étudie l’impact des facteurs, induits par les mesures mises en place pour faire face à la pandémie de Covid-19, sur les probabilités de variation des caractéristiques d’un travail qui a du sens. Divers facteurs induits par la pandémie ont été examinés : le télétravail, la situation d’emploi et le fait de considérer la pandémie comme un événement marquant. La collecte de données a été effectuée au moyen d’un questionnaire en ligne entre novembre 2022 et mars 2023 auprès de 166 personnes adultes francophones du Québec ayant au moins cinq années d’expérience professionnelle. Les résultats mettent en lumière que la pandémie a influencé des caractéristiques d’un travail qui a du sens, particulièrement lorsque l’activité professionnelle est exercée en télétravail total, lorsqu’il y a un changement de situation d’emploi, lorsqu’il y a une inactivité de travail prolongée et lorsque la pandémie est considérée comme un événement marquant.

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 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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.246
Threshold uncertainty score0.488

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.041
GPT teacher head0.320
Teacher spread0.279 · 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.

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

Citations1
Published2024
Admission routes2
Has abstractyes

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