Weaving and Unraveling Dominance: A Critical Analysis of Personal and Professional Social Work Identities in Alberta, Canada
Bibliographic record
Abstract
This thesis reports on findings from a critical qualitative study exploring and challenging normative notions of what it means to be a social worker.Throughout this thesis, I investigate how practicing social workers in Alberta negotiate their personal and professional identities.Drawing on 22 transcripts from semi-structured interviews with 11 unique participants, I analyze discursive strategies that are used to define and categorize what social work is and who social workers are expected to be.Grounded in critical and anti-oppressive theories and methodologies -namely Critical Disability Studies and Critical Discourse Analysis -I critique how dominance and power are woven into narratives of identity, belonging, and pride within the interview data.In particular, I critically illustrate how being a social worker is constructed in opposition to being a client.I conclude by reflecting on what social work could become when the rigid exclusionary boundaries of the profession are unraveled and reimagined.I would like to gratefully acknowledge the enormous contributions of my supervisor, Dr. Pamela Grassau, and my committee member, Dr. Kelly Fritsch.You have carved out and protected space for me to bring so much of myself to this work.Kellythank you for broadening my knowledge and understanding of disability and for pushing this work far beyond the expanses I ever imagined possible.Thank you for your considerate questions, critique, and feedback.Pam -thank you for taking care of me and my work, for being my fiercest
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.066 | 0.038 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".