Principles for the consideration of intersectionality in place‐based disaster risk governance in islands
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
Abstract This paper advances disaster risk governance (DRG) research and practice by incorporating elements of intersectionality and place‐based thinking. Intersectionality provides a crucial yet underutilised lens to examine power, positionality, and individuals' experiences facing disasters and other climatic events. Through six principles and using examples from small islands and a synthesis of the literature, this paper presents an intersectional approach for DRG to support inclusive and contextualised actions: (i) individuals are multi‐dimensional and complex; (ii) identities and vulnerability are not predefined; (iii) spatial and temporal differences influence the expression of identities; (iv) materiality of ecological systems influences intersectionality; (v) power relations are central the emergence of social processes and epistemologies; and (vi) positionality plays an important role in defining risk reduction agendas and choices. This paper examines how an intersectional perspective generates pathways to address the root causes of vulnerabilities to disasters beyond the ‘one size fits all’ approaches promoted globally.
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 | 0.002 | 0.000 |
| 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 | 0.000 | 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