The Official Development Assistance Accountability Act: Global Justice and Managerialism in Canadian Law
Bibliographic record
Abstract
The creation of the ODA Accountability Act was championed by a small group of activists who wanted Canadian aid to respond to global injustices, understood in terms of poverty, inequality, and human rights violations. Nevertheless, the political debate surrounding the ODA Accountability Act was largely a domestic affair, in which almost all of the participants were Canadian. The proponents of the Act employed a number of strategies to overcome this democratic deficit. Foremost among these strategies was an appeal to a managerial conception of development assistance. Another important strategy was the incorporation of norms and standards borrowed from international organizations. This article argues that neither of these approaches provides a satisfactory response to democratic concerns.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.023 | 0.016 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".