The Role of Social Research in Effective Social Change Programs
Bibliographic record
Abstract
Abstract Social research is a critical foundation for programs that seek to engage communities in change and in the development of more sustainable societies. Without appropriate research, programs aimed at change are likely to be based on implicit or assumed problem identification and/or inferred community needs and wishes. If we are to achieve community participation in activities that lead to real change, research to find out about those communities is the first step. Over the past ten years the NSW Department of Environment and Conservation (DEC) has developed a considerable body of social research, conducted with both the general community and specific community segments, to underpin its environmental education programs. This paper includes a review of some models for integrating social research into education programs, and examines the extent to which social research has impacted on both the environmental education programs and the organisational culture of the DEC. From this are drawn learnings from the perspective of a major State environmental agency, about the integration of social research into any program or organisation seeking to achieve social change towards sustainability. As well as program specific benefits, the ultimate outcome of this process is to assist in producing an organisational culture which values evidence-based decision-making and develops policies and structures that incorporate a social research dimension into both programs and policy.
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 | 0.286 | 0.223 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.006 |
| Science and technology studies | 0.021 | 0.083 |
| Scholarly communication | 0.028 | 0.022 |
| Open science | 0.004 | 0.038 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".