Interaction, ratés de l’intercompréhension et identité professionnelle: traces discursives du social
Bibliographic record
Abstract
Following a brief background of the interactional paradigm in language sciences, our purpose in this article is to demonstrate the usefulness of an interactional analysis anchored in the discursive traces left by “intercomprehension failures.” A failure of this kind reveals the non-coincidence between interlocutors’ expectations as well as the non-coincidence of their interpretation of what is said to them in a given situation. Two reports of intervention produced during a work meeting in a Quebec birthing centre are analyzed. The results show that the intercomprehension failure in this situation results because the speaker who produced the reports – a student midwife – does not possess the implicit knowledge shared by the official midwives and consequently fails to adequately select the elements that should figure in the report. This incomplete appropriation of implicit knowledge is the mark of a professional identity in the process of its acquisition. --- Original in French.
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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 | 0.012 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".