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Record W2298151869 · doi:10.24043/isj.252

Participatory Action Research for Dealing with Disasters on Islands

2011· article· en· W2298151869 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueIsland Studies Journal · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsParticipatory action researchCitizen journalismAction (physics)Context (archaeology)Disaster researchAction researchSociologyPolitical scienceGeographyArchaeologyLaw

Abstract

fetched live from OpenAlex

Much disaster research has a basis in non-island case studies, although monodisciplinary disaster-related research across past decades has often used case studies of individual islands. Both sets of work contribute to contemporary ‘participatory action research’ which investigates ways of dealing with disasters on islands. This paper asks what might be gained through combining disaster research, island studies, and participatory action research. What value does island studies bring to participatory action research for dealing with disasters? Through a critical (not comprehensive) overview of participatory action research for dealing with disasters on islands, three main lessons emerge. First, the island context matters to a certain degree for disaster-related research and action. Second, islandness has much more to offer disaster-related research than is currently appreciated. Third, more studies are needed linking theory to evidence found on the ground on islanders’ terms. Limitations of the analyses here and future research directions are provided.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.629
GPT teacher head0.521
Teacher spread0.109 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it