Exploring the Roles of Environmental Non-Governmental Organisations in the Context of Malaysian Climate Change Governance
Bibliographic record
Abstract
As non-state actors, environmental non-governmental organisations (ENGOs) are able to influence the governance process in many cases. Although the ENGOs role in climate change governance has been extensively studied over the last two decades, there is a dearth of research relating to Malaysian ENGOs. Accordingly, this study was conducted to compensate for this gap in the literature, and it employs a qualitative approach via analysis of relevant documents and in-depth interviews with eleven ENGO informants operating in Malaysia at national, sub-national and local levels. The informants were selected through purposive sampling, and the interview data were analysed using thematic analysis. The informants described the ENGO roles in climate change governance at national, sub-national, and local levels, and their roles were described in the context of the following six key themes: political, informational, educational, complementary, observational, and innovational. Similar to earlier perspectives, the results of the present study revealed that the government generally accepts the ENGOs’ role to facilitate climate change governance. This article provides insight into the ENGO’s role in assisting the government in governing climate change in Malaysia.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".