Embodied Knowledge: A Reflexive Account of Negotiating and Integrating Insider–Researcher–Practitioner Identities During a Bereavement Study
Bibliographic record
Abstract
Embodied knowledge and grief are often unaddressed in academic training and education. This article presents a reflexive and critical account of the author’s experience conducting a qualitative study on bereavement accommodation as an insider, researcher, and practitioner. Approaching herself as an object of inquiry, she considers the way her identities engage with the knowledge being generated, and the discrepancy between the values she was promoting in her work and the pressures to replicate ideologies about productivity and autonomy. The author outlines a methodological approach that applies feminist ethics beyond the data to account for the researcher and research process. The implications of placing care at the center of the labor process are discussed, including: (a) attending to embodied knowledge, interdependence, responsibilities, and invisible labor, (b) developing, implementing, and evaluating a care plan, (c) distinguishing participant and researcher voices, and (d) contributing to collective efforts to enhance bereavement care and education.
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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 | 0.055 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.018 | 0.149 |
| Scholarly communication | 0.026 | 0.027 |
| Open science | 0.005 | 0.022 |
| Research integrity | 0.008 | 0.010 |
| 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".