Navigating the Student Affairs Landscape: An Autoethnographic Exploration of the Student Affairs Profession from Canadian Perspectives
Bibliographic record
Abstract
This autoethnographic study examines the evolving professional landscape of student affairs in Canada through the lived experiences of five scholar-practitioners. Drawing on reflective narratives and thematic analysis, the study explores three central themes: unplanned career entry into student affairs, the expanding and complex demands placed on practitioners, and the dynamic construction of professional identity. Framed by the job demands-resources model and social ecological systems theory, this research reveals how intersecting personal, institutional, and systemic forces may shape the careers and commitments of student affairs professionals. Findings highlight tensions between credentialism and experiential knowledge, the emotional toll of equity work, and the precarity of institutional belonging. This article offers a nuanced understanding of the student affairs profession and calls for more inclusive, relational, and critically reflexive approaches to professional development, institutional policy, and workforce sustainability. It contributes to emerging discourses on practitioner well-being, professionalization, and systemic transformation in higher education.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.038 | 0.024 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".