A picture of change: using photovoice to explore social and environmental change in coastal communities on the Andaman Coast of Thailand
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
Coastal communities experience a wide array of environmental and social changes to which they must constantly adapt. Further, a community's perception of change and risk has significant implications for a community's willingness and ability to adapt to both current and future changes. As part of a larger study focusing on the adaptive capacity of communities on the Andaman Coast of Thailand, we used Photovoice to open a dialogue with communities about changes in the marine environment and in coastal communities. This article presents the results of two exploratory Photovoice processes and discusses prospects for using the Photovoice method for exploring social and environmental change. Changes examined included a number of broader environmental and social trends as well as ecological specifics and social particularities in each site. Participants also explored the social implications of environmental changes, the impacts of macro-scale processes on local outcomes, and emotive and active responses of individuals and communities to change. Photovoice is deemed a powerful method for: examining social, environmental, and socio-ecological change, triangulating to confirm the results of other scientific methods, revealing novel ecological interactions, and providing input into community processes focusing on natural resource management, community development, and climate change adaptation.
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 | 0.001 |
| 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 it