What Differences between Parents 'and Teachers' Views about their Relationships in Québec (Canada)
Bibliographic record
Abstract
Over the past 50 years, a consensus emerged from the scientific literature regarding the positive effects of school, family and community partnerships on school achievement.However, researchers noted that the implementation of these partnerships still gives rise to tensions on the ground.This research tackled with how parents and teachers get involved in the school-family-community cooperation process to support pupils at the elementary school (age 6 to 12).The goal of this paper is to compare on the one hand, the parents' views in their narratives on parents and teachers practices, and on the other hand, the teachers' views in their narratives on parents and teachers practices as well, to gain insight on the tensions characterizing these partnerships and on the possible solutions set forth by these actors.To this end, the empirical analyses are based on a approach with qualitative interviews among 14 teachers and 45 parents of pupils at six elementary schools in the Greater Quebec City area.To this end, interviews were conducted with 14 teachers and 45 parents of pupils at six elementary schools in the Greater Quebec City area.The results suggest that practices such as school-family communication or homework are privileged among parents and teachers.The analyses also suggest that parents and teachers diverge over the tools teachers use to support parents involvement.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".