Exploring Social Justice Advocacy in Dietetic Education: A Content Analysis
Bibliographic record
Abstract
PURPOSE: To explore the extent to which knowledge- and skill-based learning regarding social justice and/or social justice advocacy is included in the course descriptions of required courses of accredited, English-speaking dietitian training programs in Canada. METHODS: This study is a mixed-methods content analysis of required course descriptions sampled from university academic calendars for accredited, English-speaking dietitian training programs across Canada. RESULTS: Quantitative analysis showed that required course descriptions (n = 403) included few instances of social justice-related terminology (n = 63). Two themes emerged from the qualitative analysis: competing conceptualizations of social issues and dietitians' roles; prioritization of science-based knowledge and ways of knowing. CONCLUSIONS: Accredited, English-speaking dietitian training programs in Canada appear to include little knowledge- or skill-based learning regarding social justice issues and advocacy. Supporting future dietitians to pursue leadership roles in redressing social injustices and socially just dietetic practice may require more explicit education and training about social justice issues and advocacy skills.
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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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".