“As Far as Possible and as Appropriate”: Implementing the Aichi Biodiversity Targets
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Past shortfalls to meet global biodiversity targets have simultaneously prompted questions about the relevance of global environmental conventions, and sparked renewed ambition, for example, in the form of the Aichi Biodiversity Targets. While progress toward the Aichi Targets through the Convention on Biological Diversity is well‐documented globally, less is known at the national level. We conducted a systematic content analysis of 154 documents to assess the nature and extent of national implementation of the Aichi Targets using Canada as a case study. Results indicate that most responses are aspirational, with only 28% of responses implemented. Implemented responses tend to be associated with targets with specified levels of ambition that emphasize biophysical values, or targets that are relatively straightforward to achieve in this context (e.g., knowledge capacity and awareness). In contrast, targets focused on equity, rights, or policy reform were associated with fewer actions. Implementation of this latter class of targets is arguably stalled not solely because of a lack of effective target design, but because of lack of fit within existing institutional commitments. This suggests that solutions—in terms of improving implementation—lie not only in overcoming known dilemmas of quantifiability, but also in fostering institutional transformation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 it