Plants and the Kunming-Montreal global biodiversity framework: educational approaches to support pro-conservation behaviours
Bibliographic record
Abstract
The COP15 Kunming-Montreal Global Biodiversity Framework (GBF) aims to address rapid biodiversity loss and protect 30% of the planet for nature by 2030. Biology education could help to engage citizens with the GBF and promote pro-conservation behaviours, particularly for plants, which have historically been neglected in education and biodiversity conservation. In this narrative review and critical commentary, we consider what kind of approaches could lead to pro-conservation behaviour towards plants in support of the GBF, at school and tertiary levels of biology education. We examined twenty-two experimental studies about plant ecology and education, published in indexed journals from 1998 to 2022. The prevalent approaches were ecological gardening, informal science education and authentic enquiry. We assess the studies for the capabilities, opportunities and motivations provided by the pedagogic design and present behavioural models of how the approaches might support citizens’ pro-conservation behaviours, based on study findings. We discuss how the approaches might support the goals of the GBF, barriers to implementation and recommendations for overcoming these.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.023 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| 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 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".