MétaCan
Menu
Back to cohort
Record W2319484263 · doi:10.24043/isj.292

Opening up the island: a ‘counter-islandness’ approach to migration in Malta.

2014· article· en· W2319484263 on OpenAlexaffvenue
Nathalie Bernardie‐Tahir, Camille Schmoll

Bibliographic record

VenueIsland Studies Journal · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicIsland Studies and Pacific Affairs
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsMobilitiesEconomic geographyImmigrationGeographyArticulation (sociology)Settlement (finance)HomogeneousSociologyGender studiesPolitical scienceSocial scienceLawComputer science

Abstract

fetched live from OpenAlex

This paper is based on qualitative research undertaken since 2010 with African immigrants living in the small island state of Malta. Its purpose is to deconstruct a number of discourses and preconceptions about irregular migration, migrants and islandness. We argue that, in order to better understand the situation of migrants in Malta, we have to engage critically with conventional wisdom that depicts (usually small) islands as isolated, immobile and homogeneous spaces. Using a spatial approach, we propose the term ‘counter-islandness’ to describe a migration situation characterized by movement (versus immobility) and articulation of scales (versus isolation). We show how different scales in their complex and multiple interactions contribute to shaping and determining the future and trajectories of the ‘undesirables’. We explain how Malta has found itself at the heart of a complex circulatory system, articulating mobilities operating at various scales. We then categorise the role of the island within migratory patterns into three different forms: the island as barrier, hub, and place of settlement.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0120.019
Scholarly communication0.0060.007
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.043
GPT teacher head0.330
Teacher spread0.287 · 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 source (direct Gemma or distilled Codex), 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

Citations48
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueIsland Studies JournalSame topicIsland Studies and Pacific AffairsFrench-language works237,207