Bibliographic record
Abstract
The author auto‐ethnographically reflects on the emotional struggle with her father's death. The haunting memory of their last conversation empowers her during the lengthy mourning process. She ‘reconstructs the event so that it can be integrated into her life story’ [J. H. Harvey (1996) Embracing Their Memory: Loss and Social Psychology of Storytelling, Allyn & Bacon, MA, p. 191]. Memories of their relationship resurface as the emotional landscape involves love, strength, denial, compassion, withdrawal and helplessness. The reflection explores the educative process of writing from the heart. It also shares multicultural funeral rites and how they differ from traditional North American funerals. At a deeper level, writing the auto‐ethnography becomes cathartic as it helps ‘break ties between the bereaved and the dead to achieve a good adjustment’ (Ibid., p. 138). It also explores theory, practice, and innovation that embed voices in health and education in order to enlighten practice. In the end, reflecting on the memory of her father's last words becomes a transformative educational process as it provides a heightened awareness about grief, loss, bereavement and the importance of the father–daughter relationship.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".