Future Teachers’ Identity: Between an idealistic vision and a realistic view (Identité personnelle et professionnelle chez les futurs maîtres: Vision idéaliste ou regard réaliste?)
Bibliographic record
Abstract
ABSTRACT. This study focuses on the way in which graduating student teachers represent themselves both as individuals and as future professional teachers, and compares these representations by identity status as defined by Marcia (Marcia et al., 1993). Seventy-six semi-structured interviews were conducted with students during their last year of a university elementary teacher preparation program. The results show consistency between personal and professional attributes among all the interviewed students. A high number of participants see themselves as both dynamic and empathic, thus reflecting an idealized conception of themselves and of the profession. Identite personnelle et professionnelle chez les futurs maitres: Vision idealiste ou regard realiste? RESUME. Cette recherche se penche sur les representations que des etudiantes en fin de formation des maitres au prescolaire et au primaire ont d’elles-memes en tant que personnes et en tant que futures enseignantes. Soixante-seize entrevues semi-dirigees ont ete realisees dans quatre etablissements universitaires. Ces donnees sont analysees selon les etats identitaires des sujets tels que definis par Marcia (Marcia et al., 1993). Les resultats montrent une coherence entre les caracteristiques personnelles et professionnelles que les sujets s’attribuent quel que soit leur etat identitaire. Un grand nombre d’etudiantes se definissent comme dynamiques et empathiques, ces caracteristiques refletant une representation idealisee d’elles-memes aussi bien que de la profession enseignante.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".