Honouring Grief Experiences in Life, Death, and the Workplace: A Critical Analysis of Bereavement Accommodation for Workers in Precarious Employment in Canada
Bibliographic record
Abstract
Bereavement scholarship predominantly explores psychological aspects of grief, which neglects the role of social, economic, and political factors that shape the space allotted to accommodate these experiences. The current Canadian social context offers minimal space to honour bereavement as a part of the human condition. Aiming to respond to calls for enhancing bereavement care, this dissertation explores bereavement accommodation for workers in precarious employment in Ontario, Canada. Drawing on critical qualitative research and feminist ethics, this study employs policy analysis and in-depth interviews to generate multi-scalar knowledge on the everyday experiences of bereaved workers in precarious employment. I argue that there are discrepancies between how bereavement is represented in the social context and the everyday experiences of bereaved workers. The current representation portrays bereavement as a short-term, workplace disruption, neglecting grief and many forms of practical and emotional labour in bereavement. Participants expressed they were uninformed and unprepared for grief and bereavement labour, and that navigating the current context created tension, stress, exhaustion, isolation, and stigma. I argue we need a collective, ontological reckoning with our sense of autonomy, recognizing and honouring our interdependence in life and death. I argue that bereavement is a neglected public health issue driven by socio-political forces that devalue relationality, stigmatize emotions, and render bereavement an individual responsibility. This thesis makes broad recommendations for a public health approach to bereavement care, including enhancing grief literacy, creating more responsive care pathways and strategies for addressing individual and collective grief, and establishing safeguards for precarious workers.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.067 | 0.034 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.009 |
| 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".