The Construction of Professional Identity of Beginning University Teachers - Two Cases Studies from Tunisia
Bibliographic record
Abstract
This article examines the relationship that may exist between the “link to knowledge” and “professional identity” which refers to the process through which the beginning university teacher can or cannot identify himself professionally. These different relationships determine the identity construction process of beginning university teachers, which is constructed in and through his experience. We used the study of “case by case” and “one by one” (Terrisse, 2009) within a clinical didactic methodology. It is about an in depth study of a “singular, divided and subjected” subject which relies on qualitative study method”. The data analysis is organised through three important tenses: the already-there, the test and the post-stroke”. The originality of our study is to analyse the identity construction process of two beginning university teachers in the region of Tunis, through a crossed case study. The in situ observation of four theoretical, the semi-structured interviews (a priori, ante and post session and post-stroke) and the continent analysis, allow us to unveil the mechanism (conscious and unconscious) of the identity construction of these beginning university teachers as well as its evolutionary and moving dynamics especially at the first years in teaching job. https://doi.org/10.26803/ijlter.17.7.8
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".