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Record W4406207233 · doi:10.1093/jrs/feae091

Performing, contesting, and resisting internal bordering of refugee rights in Costa Rica

2025· article· en· W4406207233 on OpenAlexafffund
Tanya Basok, Guillermo Candiz

Bibliographic record

VenueJournal of Refugee Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsUniversity of Windsor
FundersSocial Sciences and Humanities Research Council of CanadaGovernment of Canada
KeywordsRefugeePolitical scienceGender studiesSociologyCriminologyLaw

Abstract

fetched live from OpenAlex

Abstract While Costa Rica has witnessed an increase in refugee claimants, its policy responses have not been sufficiently studied. This article begins to fill this gap by documenting and analyzing the treatment of displaced people in search of protection in this country. Based on the fieldwork conducted in 2023 with refugee claimants and representatives from NGOs and international organizations, combined with the analysis of media coverage, reports, and available official statistics, the article analyzes the impact of Costa Rica’s internal bordering measures and practices on asylum seekers. As documented in the article, refugee claimants find themselves in an ‘eternal’ wait, lacking access to jobs and social protections, and pressured to abandon their claims. The article also highlights the dynamics of resistance and negotiation among various actors and nonperformance of internal bordering practices by state officials. We conclude that internal refugee bordering is a complex, inconsistent, and contradictory process reflective of tensions between hospitality and hostility toward displaced people in search of protection.

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)0.004
metaresearch head score (Gemma)0.005
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 score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.009
Scholarly communication0.0040.001
Open science0.0010.006
Research integrity0.0010.001
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 head0.024
GPT teacher head0.367
Teacher spread0.344 · 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

Citations7
Published2025
Admission routes2
Has abstractyes

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