A humanitarian organization in action: organizational discourse as an immutable mobile
Bibliographic record
Abstract
Following Alvesson and Kärreman's (2000) influential essay on the modes and interpretation of organizational discourse, this article reports on a longitudinal study of naturally occurring interactions that took place before, during, and after a meeting between representatives of Médecins sans Frontières (Doctors without Borders), a well-known humanitarian organization, and representatives of local health centers in a region of the Democratic Republic of Congo. This episode is used to exemplify the fruitfulness of adopting a view that incorporates two dimensions of discourse, that is, what Alvesson and Kärreman identify as its transient (autonomous) and muscular (determining) nature. The longitudinal aspect of our study allows us to show what interactants accomplish in particular settings, while illustrating a crucial aspect of the trans-local dimension of their talk. As shown in this article, a given Discourse must be embodied, materialized or even incarnated in discourses, that is, tokens of text or talk, in order for it to be reproduced, sustained and transported from one point to another, that is, to become what Latour (1987) calls an immutable mobile . A given Discourse can thus maintain its shape across time and space only if a lot of interactive work is done to assure the stability of its associations in the ordinary day-to-day activity of the people who embody it.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.015 | 0.059 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.003 |
| 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 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".