Emigration of Scottish Steelworkers to Canada: Impacts on Social Networks
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".