First-hand experience of extreme climate events and household energy conservation in coastal Cambodia
Bibliographic record
Abstract
The link between household energy conservation and climate change is clearly identifiable, although energy consumers may not necessarily recognize the connection. Conservation of household energy has been conceptualized as a consequence of various reasons including pro-environmental behaviour, financial or habitual, and as a response to first-hand experience of climate hazards. While previous research has overly focused on the relationship between pro-environment and energy conservation at the household level, only few studies have examined the relationship between past experience of climate hazards such as droughts, storms and floods and household energy conservation, in the context of developing countries. Using complementary log-log regression analysis, this study aims to examine the association between first-hand experience of extreme climate events and household energy conservation behaviour among coastal residents in Cambodia. The results suggest that first-hand experience of climate hazards has positive association with reduced energy consumption by households in coastal communities in Cambodia. Furthermore, awareness of climate change influenced household energy conservation. Individuals who noticed changes in ambient temperature changes as well as changes in rain fall season over the past five years were more likely to reduce household energy consumption. Likewise, those who indicated that climate change is occurring rapidly were more likely to reduce energy consumption. On the whole, women and rural residents were less likely to report household energy reduction. While individual actions are necessary and constitute the significant first step in reducing energy consumption, policies aimed at shifting public actions towards sustainable energy use must reinforce beyond household level to ensure energy efficiency.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".