Public organizations and biodiversity disclosure: Saving face to meet a legal obligation?
Bibliographic record
Abstract
Abstract The biodiversity disclosure practices of sub‐national governments remain understudied and poorly understood. The present study investigates the biodiversity disclosure practices of the 101 public organizations in Québec, Canada. The study's purpose is to better understand the internal dynamics that may explain the various shortcomings observed in official documents. To meet this objective, Goffman's dramaturgical frontstage/backstage analogy is used. In particular, the current study employs a content analysis of the sampled organizations' action plans and annual reports ( N = 505) as well as interviews ( N = 35). The results highlight both significant gaps in Québec's public organizations' biodiversity disclosure practices and a tendency for these organizations to make symbolic rather than substantial commitments. Also, problematic behaviors that can affect transparency were identified among the organizations—specifically, bricolage of actions and the manipulation of figures to influence stakeholder perceptions.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".