Étudiants-maîtres et diversité : quelles expériences, attitudes et croyances?
Bibliographic record
Abstract
This thesis presents the results of a descriptive and exploratory study conducted with eight student-teachers preparing to teach English as a second language at McGill University in Montreal, Quebec. The purpose of this study was to explore the attitudes, experience and beliefs of the student-teachers towards diversity (sexual, ethnic, linguistic, economic, religious, etc.). The notion of intercultural education as promoted by the Quebec Ministry of Education and elaborated by Fernand Ouellet (2002) was used as a theoretical framework. Analysis of the qualitative data shows a misunderstanding of the term intercultural education by the student-teachers, but a positive attitude towards diversity. However, the participants of this study, when presented with situations dealing with discrimination, do not know how to solve the problems. They do not always fight homophobic discrimination, fearing complaints from parents or the school principal, although they act to counter racist or sexist forms of discrimination. Student-teachers tend to believe that a school teacher should not express opinions in the classroom or participate in debates. Finally, student-teachers expressed a number of criticisms towards the teaching program at MGill University.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".