Le developpement international, les ONG religieuses et les personnes homosexuelles : le cas de Crossroads Christian Communications en Ouganda
Bibliographic record
Abstract
Le 10 février 2013, les médias révélaient qu'une organisation religieuse décrivant l'homosexualité comme une « perversion » et un « péché » recevait du financement du gouvernement canadien pour du travail de développement en Ouganda.S'ensuivit un débat sur la légitimité de financer les projets de cette organisation non gouvernementale (ONG).Dans ce qui suit, nous identifions quelques enjeux éthiques soulevés par ce cas : les risques associés aux croyances et valeurs défendues par les ONG pour les personnes homosexuelles en Ouganda; le lien entre le financement d'ONG par les gouvernements et la promotion de certaines valeurs; l'étendue et les limites de la liberté religieuse des ONG.On February 10, 2013, news broke that a religious organization describing homosexuality as a "perversion" and "sin" was receiving funding from the Canadian government for development work in Uganda.There followed a debate on the legitimacy of funding the projects of this non-governmental organization (NGO).In what follows, I identify some of the ethical issues raised by this case: the risks associated with beliefs and values espoused by NGOs for homosexuals in Uganda; the link between government funding of NGOs and the promotion of certain values, and the scope and limits of religious freedom of NGOs.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".