Bibliographic record
Abstract
Social work students face a challenging and ever-changing work environment, with a less than supportive neoliberal political climate and ingrained expectation to cope in very stressful situations (Baines, 2011).The high incidence of both burnout and compassion fatigue is well documented and research suggests that shame might play a contributing role (Zapf et al, 2001;Gibson, 2014).In recent years, shame has attracted increased research attention, with findings consistently demonstrating the pervasive and harmful impact of the emotion (Gibson, 2014;Hahn, 2000).Using grounded theory and narrative inquiry methodologies; this thesis study presents the experiences, thoughts and perceptions of shame in 13 female social work students.Participants viewed shame as an incredibly painful feeling, linked to a desire to hide and a sense of powerlessness.They connected their experiences of shame to both their gender and professional identities.Participants identified gendered societal and cultural expectations as significant shame triggers.Furthermore, they attributed the undervaluing of social work as a profession and negative stereotypes about the profession as contributing to shame about their professional identity.Participants provide insights into the challenges and strengths of attending Carleton University's School of Social Work, including both the benefits and potential shame resulting from consistent reflection and awareness of their social location.Considerations for social work education programs and avenues for future research are discussed.
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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 | 0.018 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| 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".