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Record W4404291329 · doi:10.1177/10443894241276563

Community Leaders’ Perceptions of the Unique Service Barriers and Facilitators Among Immigrant Families With Young Children in the Rural U.S.–Mexico Border Region

2024· article· en· W4404291329 on OpenAlexaff
Anayeli López, Megan Finno-Velasquez, Sophia Sepp, Vanessa Mendoza, Marianna Corkill, Michelle Salazar Pérez

Bibliographic record

VenueFamilies in Society The Journal of Contemporary Social Services · 2024
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsEducation and Early Childhood Development
FundersW.K. Kellogg Foundation
KeywordsImmigrationPerceptionService (business)SociologyPsychologyEconomic growthPolitical scienceBusiness

Abstract

fetched live from OpenAlex

The present descriptive phenomenological study examines the unique service access barriers and facilitators of immigrant families along the rural U.S.–Mexico border from the perspectives of agency and government representatives. Twenty-three semi-structured interviews were conducted with nine local/state government officials and 14 community agency leaders using purposive and snowball sampling. A phenomenological thematic analysis approach was utilized to analyze data from individual interviews. Findings reveal that unique barriers experienced by immigrant families in the U.S.–Mexico border region include rurality, border checkpoints, and U.S. Customs and Border Patrol presence, which have placed mobility limitations on immigrant families, cutting them off from central service providers. Programs and policies aimed at engagement of mixed-status families in areas along the U.S.–Mexico border need to create mechanisms to better reach these families.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.027
GPT teacher head0.340
Teacher spread0.313 · 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.

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

Citations4
Published2024
Admission routes1
Has abstractyes

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