Bibliographic record
Abstract
L’apprentissage en famille, l’« ecole a la maison » ou le homeschooling est un choix educatif alternatif qui permet au parent de prendre en charge l’education de son enfant d’âge scolaire en remplacement de la frequentation a temps plein d’un etablissement scolaire. La recherche scientifique sur l’apprentissage en famille est emergeante et principalement conduite et publiee dans des contextes anglophones. Cet article propose une breve note de synthese de la litterature scientifique recente et internationale sur l’apprentissage en famille afin d’en identifier les dimensions etudiees et les connaissances actuelles. Les themes abordes sont les suivants : l’historique, le portrait actuel, la place dans la societe et les enjeux de l’apprentissage en famille. THE FAMILY LEARNING APPROACH: A CONCEPT NOTE The family learning approach, home education, or homeschooling is an alternative pedagogical choice that enables parents to take charge of their school-aged child’s education by replacing full-time school attendance. Scientific research on the family learning approach is emerging and mainly conducted and published in English-speaking contexts. This article presents a brief concept note of recent and international scientific literature on the family learning approach in order to identify studied dimensions and current knowledge. The following themes are addressed: history, current picture, place in society, and issues of the family learning approach.
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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| 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".