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Record W2114251905 · doi:10.1177/0950017013491453

Recruitment processes and immigration regulations: the disjointed pathways to employing migrant carers in ageing societies

2013· article· en· W2114251905 on OpenAlexfundno aff
Alessio Cangiano, Kieran Walsh

Bibliographic record

VenueWork Employment and Society · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
FundersEconomic and Social Research CouncilUniversity of GalwayNuffield FoundationUniversity of OttawaAtlantic Philanthropies
KeywordsImmigrationDemographic economicsAgeing societyBusinessEconomic growthPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Older adult care in Ireland and the UK has seen substantial recruitment of migrant registered nurses and care assistants. However, there is little information on recruitment methods in this sector and on how the current immigration systems influence these strategies. This article aims to address this topic through a survey of care organizations and interviews with employers and migrant carers in Ireland and the UK. Recruitment of migrant carers is based on a combination of conventional approaches, informal networks and recruitment agencies. Choice of strategy is dependent on occupation type and the targeted labour pools. Findings demonstrate that immigration regulations effectively dictate the recruitment pools and shape employer recruitment methods.

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)0.029
metaresearch head score (Gemma)0.060
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 score0.029
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.060
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.011
Scholarly communication0.0050.004
Open science0.0020.011
Research integrity0.0020.002
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 head0.288
Teacher spread0.245 · 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

Citations30
Published2013
Admission routes1
Has abstractyes

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