Bibliographic record
Abstract
Abstract: The author reflects on the death of professor who was on her doctoral committee. She considers how “grief and bereavement has undergone a transformational change in terms of how the human experience of loss is understood, “(Hall, 2014, p. 7). The article explores how “poems are powerful documents that possess the capacity to capture the contextual and psychological worlds of both poet and subject,” (Furman, 2007, p. 302). It also explores how reflexivity can be enacted through a poetic inquiry (Prendergast, Leggo, Sameshima, 2009). Thus, the narrative can contextualize “using alternative forms of data to evoke deep and powerful emotional reactions in the consumer of research,” (Denzin, 1997). In the end, the narrative weaves poetic inquiry that helps the author gain a deeper understanding about the personal and cultural influences of grief and how it transforms reflections on death, dying, life, and loss. Keywords: Death; Grief; Loss; Poetic Inquiry. Résumé : L’autrice se penche sur le décès d’un professeur qui siégeait sur son comité de doctorat. Elle examine le changement transformationnel de la « peine et du deuil au niveau de l’interprétation de la perte dans le cadre de l’expérience humaine » (Hall, 2014, p. 7). L’article décrit « en quoi les poèmes constituent de puissants documents capables de saisir les univers contextuel et psychologique aussi bien du poète que du sujet » (Furman et al., 2007, p. 302). On y apprend aussi comment la quête poétique peut donner forme à la réflexivité (Prendergast et al., 2009). Le narratif peut donc contextualiser « l’utilisation d’autres formes de données pour évoquer de puissantes et profondes réactions émotionnelles chez le consommateur de recherches » (Denzin, 1997). En bout de ligne, le narratif tisse la quête poétique qui permet à l’autrice de mieux comprendre le concept de la peine et son impact sur la réflexion de concepts tels que la mort, la vie, la fin de la vie et la perte. Mots-clés : décès, peine, perte, quête poétique.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".