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Record W1501530271 · doi:10.1002/psp.1852

Emigration of Scottish Steelworkers to Canada: Impacts on Social Networks

2014· article· en· W1501530271 on OpenAlexafffundabout
K. Bruce Newbold, Susannah Watson, Anne Ellaway

Bibliographic record

VenuePopulation Space and Place · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsMcMaster University
FundersMedical Research CouncilCanadian Institutes of Health Research
KeywordsImmigrationContext (archaeology)RecreationEmigrationPopulationSocial isolationDemographic economicsDaughterSociologyGeographyPolitical scienceDemographyPsychologyLawEconomics

Abstract

fetched live from OpenAlex

Abstract Throughout the 1960s–1980s, many steelworkers emigrated from the regions in and around Glasgow, Scotland, seeking better economic opportunities in other industrial cities, including Hamilton in Ontario, Canada. However, little is known about how this move affected the social networks of the steelworkers and their families at the time of immigration and how their social networks had evolved over time. Fifteen former Scottish steelworkers living in the Hamilton area and the daughter of one deceased steelworker were interviewed for this study. Immigration to Canada had clearly disrupted their social networks, as many experienced the loss of valued relationships with parents, neighbours, and co‐workers left behind in Scotland. These losses led to homesickness for many steelworkers and their wives and had driven some families back to their home country. Despite cultural similarities to the broader population, the steelworkers still experienced social isolation at times that limited their ability to form supportive networks (particularly with co‐workers and neighbours). Over time, a change in lifestyle as a result of immigration increased social advantages in Canada, and involvement in recreational sports contributed to the strengthening of relationships (particularly with their immediate family members and fellow Scottish immigrants) and the formation of new social networks, albeit ones that differed from those they had left behind in Scotland. This study helped to identify circumstances that both challenge and ease the formation of social networks for immigrants and contribute to our understanding of how context influences the evolution of social networks for new arrivals. © 2014 The Authors. Population, Space and Place published by John Wiley & Sons Ltd.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.020
GPT teacher head0.277
Teacher spread0.257 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2014
Admission routes3
Has abstractyes

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