Field education in crisis: experiences of field education coordinators in Canada
Bibliographic record
Abstract
Significant multi-layered challenges with delivering quality practicum experiences to social work students have led field education coordinators to release a joint statement that social work field education in Canada is in a state of crisis. This article presents the results of a two-year mixed methods study that sought to investigate and describe the challenges in order to enhance understanding of the crisis from the perspective of Canadian social work field education coordinators. The results indicate that social work education programs in Canada face four key challenges in regard to field education that can be further divided into two sections: (a) the social work practice field and (b) social work field education administration. The two key challenges associated with the social work practice field are: (a) social work practice contexts and realities and (b) practicum shortages and saturation. The two key challenges associated with social work field education administration are: (a) practicum procurement and field instructor recruitment and retention; and (b) expectations and workloads of field education coordinators. To address these challenges, collaborative development of a multi-level strategy aimed at moving beyond the current state of crisis toward a sustainable model of social work field education in Canada is recommended.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.040 | 0.009 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".