Nations on the frontlines of climate change facing mental health impacts: reviewing Small Island Developing States (SIDS) perspectives
Bibliographic record
Abstract
Despite the evident mental health needs of small island developing states (SIDS) in the context of climate change, much of the research investigating the relationship between mental health and climate change neglects to mention SIDS specifically (e.g. Ogunbode et al., 2022). In fact, in a scoping review exploring climate change and mental health (Charlson et al., 2021), the majority of studies included originated from high-income countries in the Global North (e.g. Australia (n = 34), Canada (n = 17), USA (n = 16)). This lack of representation limits the global applicability findings, and importantly, fails to give voice to communities on the frontlines of the climate emergency. There has been a study that has aimed to address the topic of this current review. For instance, Kelman and colleagues (2021) have published a thematic review synthesising literature relating to mental health and wellbeing in SIDS facing climate change. The scope of this review appears to be broad rather than narrow, as it focuses on physical health impacts in addition to mental health impacts. Furthermore, this review fails to report on the source and geographical location of authorship, making it uncertain whether SIDS voices were intentionally included. This is a critical oversight, given the inequalities that SIDS experience owing to the legacy of power imbalance bequeathed through colonialism. Given that this topic is exploratory in nature and is hoping to collate nuanced and insightful perspectives, the review will be synthesising qualitative evidence. There exists an important gap in research, highlighting the need to capture the mental health experiences of SIDS, as these nations are at the frontlines of the climate crisis. Therefore the current study will conduct a thematic literature review on this topic, focusing on experiences voiced from a SIDS perspective.
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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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.009 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".