Climate change perceptions and preparation in the United States territories in the Pacific: American Samoa, Guam, and the Commonwealth of the Northern Mariana Islands
Bibliographic record
Abstract
The association between and among climate change, preparation, and perceptions on islands is becoming more commonplace-but what about on extraterritorial land governed from thousands of miles away?This article consists of on-the-ground fieldwork and interviews speaking with decision-makers and leadership personnel in American Samoa, Guam, and the Commonwealth of the Northern Mariana Islands on the following topics: how climate change is addressed, what the general attitude on-island is towards climate change, if islands' proximities to independent countries affect the territories' preparation, and if being a part of the United States is considered an asset in planning for climate change.The results from the study show that up until very recently, climate change was not readily discussed, and, when it had been, it was often only discussed with concern for ocean life.Additionally, respondents lamented that often their non-US neighbours were able to better prepare, but US territories were either outright excluded due to their tertiary sovereignties or due to lack of representation from the Federal Government at meetings.Research herein illustrates that being a territory of the United States was considered an asset in many respects due to the hypothetical protection and funding available in the event of major disaster.An emerging theme from the study is that the American territories in the Pacific sit within the margins and periphery of climate-change planning within the United States and are behind many of their neighbours in both their perceptions and preparation efforts of the effects of a changing climate.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".