Home Education in Quebec: Family First
Bibliographic record
Abstract
In Canada, until now, no studies have focused on the practice of home education in the francophone province of Quebec. While the home-educating population in that province is tangible, it has remained largely unknown. Quebec's distinctive character on three fronts – political, historical and cultural – make the application of results from the rare Canadian studies or data from the US home-educating population seem inappropriate. This research, conducted by questionnaire in 2003, documented the sociodemographic characteristics of Quebec's home-educating families and their motivations for home education. Beginning with a portrait of Quebec's particular context, this article presents the motivations underlying the choice of home education expressed by 203 Quebec families. The reasons why these families have chosen to homeschool are many and diverse; parents' rationales for their choices are wide-ranging and multidimensional. One particularity of the results is that no religious, philosophical or anti-state viewpoint seems to dominate the combined discourse. Seven motivational factors for home education were identified. Collectively, the respondents express the following as their main motivations for home educating their children: a desire to pursue a family educational project; an objection to the organisational structure of the school system; a desire to offer curriculum enrichment; and finally, a preoccupation with their children's socioaffective development.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.000 |
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.
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".