The Impact of Post-Secondary Educational Institution Policies and Practices on Indigenous Staff Recruitment and Retention
Bibliographic record
Abstract
There is very little published research that explores employment inequities in Canadian Post-Secondary Institutes as they relate directly to Indigenous people (Chan, 2005; Doyle-Bedwell, 2008; Dua Bhanji, 2012; Julien, Wright Zinni, 2010; Singh, 2012). The primary question this study addressed was what impact, if any, did a GTA Aboriginal Post-Secondary School Educational Institute’s (APSE’s) organizational policies, practices and processes have on the recruitment, support, and retention of Aboriginal staff. The participants from the APSE included part time, full time, and Aboriginal Staffing Pilot Program (ASP) employees. Informed by Institutional Ethnography, Ojibwe Medicine Wheel and Womanist theory, the study explored the daily work experiences of the Aboriginal participants as they connected to broader social structures, processes and relationships within the organization. The findings included that the participants were disconnected from the policies enforced by the APSE. Policies were largely constructed without the consideration of Indigenous knowledges and priorities. Another finding was the lack of Indigenized culture and curriculum development erroneously reinforced the belief that Indigenous college members ought to “get over it” and conform to the College’s corporate culture. Recommendations included increasing Indigenous staff representation; consistently Indigenizing the curriculum and culture of the APSE; and cultural safety awareness training for all staff. Given the Truth and Reconciliation calls to action directly hold educational institutions accountable for the needs and inclusion of Indigenous people, the experiences, and insights explored in this study are valuable information for post-secondary Human Resources departments and senior management examining their staff recruitment and retention efforts.
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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 | 0.025 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".