Perceived Self-Efficacy and Adaptation to Climate Change in Coastal Cambodia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In response to climate change at different spatial scales, adaptation has become one of the focal points of current research and policy developments. In the context of coastal Cambodia, there is little research on local level adaptation to climate change. Using ordinal logistic and logistic regression analyses, this study examines the relationship between perceived self-efficacy and anticipatory and reactive adaptation to climate change among 1823 households in coastal communities in Cambodia. Findings indicate that individuals who reported higher categories of self-efficacy were more likely to report both anticipatory (OR = 1.74, p < 0.001) and reactive adaptation (OR = 3.61, p < 0.001) measures. Similary, tndividuals who had higher education had higher odds of reporting anticipatory adaptation (OR = 1.71, p < 0.001) and reactive adaptation (OR = 1.63, p < 0.05) when compared with those without formal education. Participants who have been living in their current residence for six years or more were more likely to report anticipatory adaptation (OR = 1.09, p < 0.05) and reactive adapation (OR = 1.22, p < 0.001) compared with those who had lived there for a shorter duration of time. Region of residence was positively associated with both anticipatory and reactive adaptation. In this context, it is important to note that individuals in the most agriculture-dependent and climate sensitive province reported the least anticipatory and reactive adaptation measures. Policy makers should target empowerment of the most vulnerable population to facilitate better adaptation behavior, and mainstreaming of knowledge on climate change adaptation through both formal and informal education at the community level.
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.
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 | 0.001 |
| 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 it