Enjoying Our Backyard Buddies – Social Research Informing the Practice of Mainstream Community Education for the Conservation of Urban Wildlife
Bibliographic record
Abstract
Abstract Supporting urban communities to make changes that contribute to sustainable living is a challenge that many environment and conservation organisations embrace. However, many community education and involvement initiatives to date have tended to appeal mostly to those with knowledge and enthusiasm for protection and conservation of the environment, leaving the majority of the community relatively unengaged. In a NSW Environmental Trust supported initiative seeking to enhance the protection and conservation of wildlife in urban environments, a major social research project was undertaken to investigate community understandings of wildlife conservation, for application to urban community education programs. The research incorporated both qualitative and quantitative methodologies to gain insights that practitioners can use to develop, monitor and evaluate urban environment and conservation initiatives that engage and involve the WIder community. This paper presents some key findings of the research and provides case examples of environmental education initiatives bringing this research into practice. The research indicates that community understandings of conservation are broad ranging. The research reveals that prominent conservation language and concepts, well understood by keen and knowledgable environmental educators, have little relevance to mainstream audiences. Other findings identify how conservation can have high relevance and meaning for the broader community as an integral part of their everyday life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.028 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.030 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".