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Record W4400777081 · doi:10.24043/001c.120295

Small Islands and Islets: Laboratories or Key Sensors for Environmental Policies in the Mediterranean Basin?

2024· article· en· W4400777081 on OpenAlexvenueno aff
Orianne Crouteix

Bibliographic record

VenueIsland Studies Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIsland Studies and Pacific Affairs
Canadian institutionsnot available
FundersUniversité de LimogesAssociation Nationale de la Recherche et de la Technologie
KeywordsDelegationGeographyMediterranean BasinEnvironmental resource managementStructural basinAgency (philosophy)Environmental planningPolitical scienceEnvironmental protectionMediterranean climateSociologyEnvironmental science

Abstract

fetched live from OpenAlex

By building the PIM Initiative, the European and International Delegation of France’s Conservatoire du Littoral et des Rivages Lacustres (Coastal Protection Agency) aims to use small islands as laboratories to unite actors and build ambitious environmental policies in the western Mediterranean basin. This study examines the position of these small islands as a relevant model for conservation policies and actions. It is based on data collected during a two-year immersion in the PIM Initiative and uses several methodological and analytical tools. While working on the small islands of the Mediterranean basin, the PIM Initiative uses three main techniques: building a collective, gathering environmental data, and spreading a representation of these territories to wider publics. These techniques are analyzed using the framework of the circulatory system of scientific facts (Latour, 1999). This analysis highlights three preconceptions: (i) small islands group a limited number of actors, (ii) islands attract and facilitate consensus, and (iii) actions implemented on small islands can be replicated on larger islands and the mainland. The article concludes by discussing how the PIM Initiative is poised between considering small islands as laboratories which should become models for environmental policies, or as key sensors, specific territories which highlighted some broader features.

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.

How this classification was reachedexpand

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.432
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
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 head0.062
GPT teacher head0.333
Teacher spread0.271 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2024
Admission routes1
Has abstractyes

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