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Record W4385755641 · doi:10.1177/00220027231195066

Changes in Perceptions of Border Security Influence Desired Levels of Immigration

2023· article· en· W4385755641 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Conflict Resolution · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsUniversity of Guelph
FundersConcordia UniversityUniversity of GuelphUniversity of Pennsylvania
KeywordsImmigrationBorder SecurityPerceptionIsolation (microbiology)Immigration policyGovernment (linguistics)Control (management)Demographic economicsPolitical scienceEconomicsPsychologyPublic administrationLaw

Abstract

fetched live from OpenAlex

Security concerns about immigration are on the rise. Many countries respond by fortifying their borders. Yet little is known about the influence of border security measures on perceived threat from immigration. Borders might facilitate group identities and spread fear of outsiders. In contrast, they might enhance citizens’ sense of security and control over immigration. We test these claims using survey experiments run on a quota sample of over 1000 Americans. The findings show that allocating more government resources to border security increases desired levels of immigration. This effect is likely driven by a sense of control over immigration, induced by border security measures even when the number or characteristics of immigrants remain unchanged. Our findings suggest that border controls, which are widely considered as symbols of closure and isolation, can increase public support for immigration.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.038
GPT teacher head0.360
Teacher spread0.323 · 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