Between the Tides: Developing an Indigenous-Informed Cultural Safety Training Impact Assessment Survey Tool for Post-Secondary Institutions on Vancouver Island, BC
Bibliographic record
Abstract
This paper highlights the development of an Indigenous Cultural Safety Training (ICST) impact assessment survey tool working in collaboration with Indigenous leaders, Elders, faculty, staff, and students from across four post-secondary institutions on the traditional lands of the Songhees, Esquimalt and WSÁNEĆ Peoples on Vancouver Island, British Columbia. What emerged from a series of Indigenous-led workshops was the development of an ICST impact assessment survey tool to measure the impact of the training as well as for ICST participants to reflect on their own cognitive and behavioural change within their practice over a 12-month period. In addition, a validation process with ICST experts, facilitators, staff, faculty, Elders, and participants was carried out to help refine the proposed co-constructed assessment variables, statements, and questions underpinning the survey tool. The finalized ICST impact assessment survey tool will not only improve the quality of ICST in post-secondary settings, but will also enable staff, faculty, and leaders to reflect on how the ICST improves their personal and professional practice working with Indigenous students in these settings.
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".