Ces experts qui venaient du froid : Comment des Canadiens deviennent experts en développement de l'Afrique subsaharienne
Bibliographic record
Abstract
Each year, hundreds of Canadian experts offer their opinions, their skills, their knowledge or know- how to implement, monitor and evaluate projects and programs aimed at developing communities in the Sub-Saharan African region. Canada is a northern country located roughly 5000 km from the nearest African shore, therefore it becomes logical to ask how foreigners can become experts in the development of African communities. Using Bourdieu's field theory, we analyze the interviews gathered in this research to show that experts must be able to accumulate, mobilize, trade or transform technological, organizational, social and expertise capitals specific to the western world. Because of that, the field of expertise in international development is in a constant struggle to reaffirm its autonomy next to the dominant fields of the western world notably the political and economical fields. /// Chaque année, des centaines d'experts canadiens offrent leurs avis, leurs compétences, leurs connaissances ou leurs savoirs-faire, afin de mettre en place, de suivre et d'évaluer des projets et des programmes destinés à développer des communautés d'Afrique subsaharienne. Le Canada étant un pays nordique situé au minimum à plus de 5000 kilomètres des côtes africaines, il devient logique de se demander comment des étrangers venus de si loin sont devenus experts du développement des communautés africaines. À partir de la théorie du champ de Bourdieu, l'analyse des entretiens menés dans le cadre de cette recherche nous indique que, pour devenir expert, il faut être en mesure d'accumuler, de mobiliser, d'échanger ou de transformer des capitaux technologiques, organisationnels, sociaux et d'expertises spécifiques à l'occident. En ce sens, le champ de l'expertise en développement international se trouve en lutte constante pour sauvegarder son autonomie vis-à-vis des champs qui dominent la société occidentale, notamment le champ économique et le champ du pouvoir.
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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 | 0.008 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.026 | 0.009 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".