Ambitious for change? A critical appraisal of the Canadian indicator framework of the sustainable development goals
Bibliographic record
Abstract
Abstract This article explores the indicators and targets identified in the Canadian Indicator Framework, a localization of the UN Sustainable Development Goals for the country of Canada. Applying a critical theoretical lens and a human rights approach, the authors explore each of the ‘ambitions’ proposed by the federal government and assess their suitability in meeting the magnitude of transformative change that will be necessary to meet the goals of the 2030 Agenda for Sustainable Development. In considering each of the Canadian ambitions proposed to realize Sustainable Development Goals 1 to 17, and the framework as a whole, the authors conclude that a business-as-usual stance has been applied. Many of the Canadian ambitions have ‘no specific target’ identified, offering no baseline measures or concrete standards from which to benchmark and monitor progress. The ones that do are not tremendously transformative, leading to a framework that does not present a dramatic departure from existing policy and practice arrangements. The character of the Canadian ambitions to the Sustainable Development Goals are revealed, not as concrete change strategies, but as mere aspirations, albeit more for the status quo than for transformational action. To translate the Canadian ambitions into actions, human rights must be infused into the Canadian Indicator Framework, and these must be substantive, de facto, rights—rights that people can actually claim, and hold state actors accountable to.
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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 | 0.109 | 0.127 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.027 | 0.025 |
| Science and technology studies | 0.030 | 0.045 |
| Scholarly communication | 0.031 | 0.010 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".