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Record W4404539468 · doi:10.24043/001c.125847

From Transport Development to Land Reclamation: Contested Spatio-Temporalities along Penang’s Littoral, Malaysia

2024· article· en· W4404539468 on OpenAlexvenueno aff
Pierpaolo De Giosa

Bibliographic record

VenueIsland Studies Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsnot available
FundersHORIZON EUROPE Framework ProgrammeEuropean Commission
KeywordsLand reclamationTemporalitiesBannerOpposition (politics)Environmental planningPolitical scienceCivil engineeringGeographyPoliticsEngineeringArchaeologyLaw

Abstract

fetched live from OpenAlex

“One island is enough” was written on a banner shaped like Penang Island, Malaysia, during a demonstration against the plan to create three artificial islands. The Penang South Reclamation (PSR) project, adopted by the local administration and developers, aims to finance the Penang Transport Master Plan (PTMP). This ambitious plan includes several components, such as monorail and light rapid transit lines. While land reclamation is not new in Penang, this mega-development project has faced unprecedented opposition from a wide range of actors. In dialogue with fishers and activists supporting the Penang Tolak Tambak (Penang Rejects Reclamation) campaign, and through the analysis of government documents, non-governmental reports, news articles, and social media, this paper traces how state, corporate, and civil society actors have shifted their focus from the PTMP to the PSR project. Thus far, scholarly literature on island environmental movements has focused on the right to the island and the right to nature, while claims related to the land-sea interfaces, which so clearly delineate island spatialities, have been somewhat neglected. By exploring the contested spatio-temporalities of this land reclamation project off the south coast of Penang, this paper expands the dialogue of the right to the island to include the right to the sea.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score0.941

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 studies0.0010.000
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 head0.172
GPT teacher head0.362
Teacher spread0.190 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2024
Admission routes1
Has abstractyes

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