Bibliographic record
Abstract
L’articulation études-famille-emploi pose des défis importants aux parents-étudiants, notamment aux mères-étudiantes. La pandémie de COVID-19 a complexifié l’articulation des sphères de vie en effritant les frontières entre elles. La présente étude expose les besoins de mères-étudiantes d’un cégep en matière d’articulation études-famille-emploi, ainsi que les stratégies institutionnelles mises en place par ce cégep pour répondre à ces besoins. Le volet collégial de l’enquête de terrain a été conduit au cours de la deuxième vague de COVID-19 au Québec. Aussi, cette étude permet d’éclairer comment a été vécue l’articulation études-famille-emploi dans ce contexte inédit. Connaitre les besoins des mères-étudiantes et les stratégies institutionnelles en matière d’articulation études-famille-emploi est important pour lever les obstacles à la participation à la formation de ces femmes, notamment les obstacles institutionnels. En ce sens, la présente étude relève d’une approche inclusive en éducation des adultes, qui est attentive à la spécificité de leurs besoins.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.021 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".