Families’ Emotion Work in Transnational Settings: The Case of Military Families
Bibliographic record
Abstract
Abstract Combining literature on transnational families, migrant workers, and expatriates, I suggest a reconceptualization of military service personnel’s labour during overseas deployment as transnational. Further, I argue that during deployments, military families are thus transnational families who experience unique issues related to their geographical separation. To illustrate this, I explore the way in which military families access information and communications technology in order to maintain relationships across geographical distances, emphasizing the emotional labour of military service personnel and their families. I conclude that conceiving of military service personnel as transnational labourers enables a more nuanced understanding of transnational labour in the context of globalization, one which acknowledges a “grey area” between an ideological dichotomy that places poor manual labourers from developing countries (migrants) in contrast to rich knowledge workers from developed countries (expatriates) with little recognition of the diversity of transnational lives in between.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.033 | 0.019 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| 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".