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Navigating the Tightrope: Immigrant Perspectives on State Policies Balancing National Interest and Humanitarian Imperatives

2025· article· en· W4409893499 on OpenAlexaboutno aff
Mirnawanti Wahab

Bibliographic record

VenueInternational Journal For Multidisciplinary Research · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationPolitical scienceState (computer science)National interestPolitical economyPublic administrationSociologyLawPoliticsComputer science

Abstract

fetched live from OpenAlex

Immigration policies are a complex balancing act between national interests (security, economy, culture) and ethical considerations (protecting vulnerable populations, upholding human rights). This research explores this dynamic from the perspective of immigrants in their new homelands. By examining their experiences and challenges, the study provides insights into these competing priorities and proposes solutions for more equitable immigration systems. Through case studies of Canada and the United Kingdom, the research investigates how immigrants, regardless of legal status, perceive the balance between a host country's rights, security concerns, economic interests, and its duty to protect vulnerable groups like refugees and economic migrants. The study reveals the direct impact of current policies on immigrants' lives, sense of belonging, and trust in government. It underscores the critical need for inclusive policymaking that incorporates immigrants' voices, fostering ethically sound systems that effectively balance national interests with humanitarian responsibilities.

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)0.010
metaresearch head score (Gemma)0.006
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 score0.031
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0220.034
Scholarly communication0.0140.008
Open science0.0010.009
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0020.000

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 head0.093
GPT teacher head0.508
Teacher spread0.415 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueInternational Journal For Multidisciplinary ResearchSame topicMigration, Refugees, and IntegrationFrench-language works237,207