DES FONDEMENTS AXIOLOGIQUES À LA PROFESSIONNALISATION DU TRAVAIL SOCIAL: : PROCESSUS DE CONSTRUCTION IDENTITAIRE CHEZ DES ÉTUDIANTS EN TRAVAIL SOCIAL
Bibliographic record
Abstract
The issue of professional identity is the object of recurrent discussions in the field of social work. One can observe a situation of discomfort among the stakeholders when they have to legitimate their practice and distinguish between this practice and other relational occupations. Taking into consideration the major influence exerted by the initial education on the construction of the professional identity of students, the way these students adhere to the representations of the profession, which are shared by the professional group in general, can provide us with relevant information regarding the development on their identity. In this research, in which we study the conceptions of social work held by social work students in a French-speaking university in Québec (Canada), our objective is to identify the impacts that the initial education have on the professional identity-building process of future social workers. Firstly, we will expose the context in which took place our research project. Secondly, we will describe the methodological approach and the analytical procedure we adopted. Thirdly, we will outline the results we obtained. Finally, in the discussion, we will deal with the identity-building process among social work students and some broader issues related to social work education.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.024 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".