Using Mobility to Gain Stability: Rural Household Strategies and Outcomes in Long-distance Labour Mobility
Bibliographic record
Abstract
Current rural studies literature is making the call for more attention to mobilities as a means to understand contemporary rurality. Mobility, envisioned broadly and inclusive of the movement of people, things and ideas, promises to position rural communities in a more active stance, rather than passive, reactive, and in receivership. Contextualized within a larger research project of 37 young women (aged 25-34) living in a rural area of central Newfoundland, Canada, and drawing specifically upon the narratives of nine return migrants with partners who engage in long-distance labour mobility, I explore how mobility is a mechanism through which these women, and their households, achieve both economic and familial stability. My research contributes to a theoretical understanding of mobility that is inclusive of, rather than juxtaposed to, stability. It also contributes to the literature on long-distance labour mobility suggesting that it is not necessarily detrimental to family life. I argue that a household mobility perspective reduces the notion of static rural society and raises new considerations for rural futures. Policy implications for a mobilities perspective are briefly discussed. Keywords: Mobility, stability, long-distance, Newfoundland, women
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".