Metrics and outcomes of conservation education: a quarter century of lessons learned
Bibliographic record
Abstract
We conducted a systematic literature review to analyze evaluations of conservation education programs on a global scale in order to better understand (1) temporal and spatial trends in conservation education program evaluations over the last 25 years, (2) patterns in the types of conservation-related issues addressed through these programs, (3) metrics that indicate effectiveness of conservation education programs, and (4) methods and timeframes used to draw conclusions about program outcomes. Findings indicated that there is a need to better connect the types of issues addressed through conservation education programs with metrics that would indicate success in addressing these issues and the actual outcomes measured and reported. As well, there is an opportunity to employ a variety of metrics and methods for evaluating program outcomes, particularly in developing countries, by focusing on cognitive and behavioral components as well as social and ecological ones. Finally, shifting to a more comprehensive strategy for evaluating multiple outcomes in different cultural contexts would provide opportunities for utilizing mixed methods and qualitative approaches in partnership with community stakeholders.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".