Bibliographic record
Abstract
Purpose – To empirically consider work and career as potential influences of suicide. Design/methodology/approach – In this qualitative study we conducted in-depth semi-structured interviews with 16 individuals who were survivors (i.e. family members or intimates) of individuals who had committed suicide. Data was analyzed using a grounded theory methodology. Findings – This exploratory study used purposive self-determination as the theoretical framework for analyzing their life histories. Factors of purposive self-determination, including lack of purpose, feeling controlled, experiencing failure, and social exclusion all figured prominently but differentially according to life-stage. Distinct work and career themes for early-career, mid-career and late-career suicides emerged. Early-career suicides were attributed to educational or work-related contexts, leading to a sense of hopelessness. Mid-career suicides emphasized despair based in failure. Finally, an attempt to escape from challenges associated with transitioning roles in retirements emerged as a key theme in late-career suicides. Originality/value – Although suicide has been studied extensively from medical, psychopathological, sociological, anthropological, philosophical and religious perspectives, there is a dearth of research considering why certain individuals choose to end their own lives as a result of work and career related reasons. This study sought to contribute to our understanding of this under-researched phenomenon. Additionally, while extant careers theory and research has considered positive notions of career such as career success or careers as a calling, this work presents an alternate lens, the consideration of career failure and careers as a sentence.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".