Une ontologie de l’empathie : la filature sensible comme méthode ethnographique affective
Bibliographic record
Abstract
Cet article explore la filature ethnographique comme méthode sensible et ontologiquement empathique, apte à restituer les dimensions affectives, matérielles et relationnelles de l’expérience vécue en contexte organisationnel. À partir d’un terrain mené auprès de huit nomades corporatifs, l’analyse met en lumière les tensions perceptibles au fil des journées observées. Une grille d’observation construite autour des perceptions sensorielles et corporelles a permis d’opérationnaliser l’ethnographie affective, en ancrant l’analyse dans une attention fine aux signaux faibles et aux atmosphères. Ce dispositif replace la filature comme une méthode à part entière, capable de rendre compte du vécu dans toute sa complexité. L’article propose enfin une réflexion sur les atouts et les limites d’une enquête empathique, notamment en ce qu’elle engage fortement la chercheuse, tant sur le plan sensoriel qu’éthique, et appelle à des formes de restitution, situées et incarnées.
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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 | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".