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Record W3120423038 · doi:10.18162/ritpu-2020-v17n3-14

Les conditions de travail à distance et le stress ressenti par les étudiants en France pendant la période de confinement

2020· article· fr· W3120423038 on OpenAlexvenueno aff
Alexandra Leyrit

Bibliographic record

VenueRevue internationale des technologies en pédagogie universitaire · 2020
Typearticle
Languagefr
FieldNeuroscience
TopicMind wandering and attention
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPolitical scienceSociology

Abstract

fetched live from OpenAlex

Cette enquête par questionnaires menée auprès de 2 570 étudiants français vise à appréhender l’effet de l’enseignement à distance, durant le confinement de 2020, sur le stress des étudiants. Elle permet, d’une part, d’analyser les conditions de travail à distance des étudiants (l’ordinateur dont ils disposent et les modalités d’accès à Internet notamment) et leur ressenti par rapport à la continuité pédagogique. D’autre part, elle permet d’analyser l’impact de ces variables sur leur niveau de stress. Ces résultats montrent notamment que, pour développer l’usage du numérique et préserver la santé des étudiants, il est important de prendre en considération l’équipement dont ces derniers disposent.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.509
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.040
GPT teacher head0.283
Teacher spread0.244 · 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.

Study designNot applicable
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

Citations6
Published2020
Admission routes1
Has abstractyes

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