Le rapport aux savoirs en lien avec le budget chez de futurs enseignants du primaire du Québec, selon trois postures épistémologiques
Bibliographic record
Abstract
Like physical and mental health, having the skills and knowledge to make responsible financial decisions can improve a person's stability and health at all levels (University of Waterloo, 2020). In some countries in the world and even in a few Canadian provinces, governments have decided to integrate some financial education concepts into elementary school education programs. This helps building skills and knowledge that can eventually lead students to conceptualize notions of financial education, such as budget planning, but can also help them to develop their financial awareness and their critical judgment in relation to consumption, by helping them understand the impact of their decisions on their personal financial situation (Government of Ontario, 2020). However, in the Quebec Education Program, there is no specific objective yet in terms of financial education at the elementary level, but teachers can decide to explore some concepts related to personal finances management, such as budget planning for example, in their lesson plans if time and capacity allows.In this research, I explore the current knowledge and perceptions of future primary school teachers in relation to teaching financial education, with a focus on knowledge around the concept of budget. This study presents an analysis of the relationship to knowledge related to the budget among future elementary school teachers in Quebec, according to three epistemological postures of teachers in training, namely the former student, the university student and the future teacher (DeBlois et Squalli, 2002)
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".