International cooperation in higher education in social work: a trainer of trainers experience
Bibliographic record
Abstract
The main aim of this article is to report the experience of the international Project “Trainer of trainers in Social Work in the Eastern region of Morocco” which has been carried out from 2009 to 2011 and was undertaken at the request of the Mohamed I University of Oujda and the social institutions of this region. This project is framed in the ART GOLD programme of UNDP, in accordance with the Millennium Goals, with the participation of the Spanish universities of Malaga, Seville and Granada, the Italian universities of Perugia and Siena, and the social partners from Spain and Italy. One of the aims of this multilateral international collaboration project is to support Mohamed Premier University in developing Social Work as a discipline by using Social Work’s distinctive areas and methodologies. Furthermore, as a social approach and as a local reinforcement, contributing to the training of social partners from local institutions and civil society. This experience highlights the risk, in the area of international cooperation in social work, of keeping Western influences, dominant positions and emphasizes the need to develop indigenous theories and practices in the developing countries. The conclusions invite us to reflect on the epistemological and methodological dimensions that indentify Social Work worldwide and its suitability to different international contexts. Key-words International Social Work, ´trainer of trainers´ in Social Work.
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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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.013 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.016 | 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".