Fathering at a distance in the military: Techniques for presence and emotion work among Canadian Armed Forces fathers
Bibliographic record
Abstract
Introduction: Military fathers aspire to be active and engaged parents, but deployments may make this difficult to accomplish. Men turn to techniques of creating presence at a distance so they can continue to father. Understanding men's experiences of fathering at a distance demonstrates how men manage work-life conflict and contributes to the sociological study of fathering in its own right. Methods: Ethnographically informed qualitative interviews were conducted with 13 Canadian Armed Forces personnel and 15 civilian spouses. Results: Fathers used techniques related to pre-planning for connecting during separations, using objects to create presence by proxy and being intentional with talk during direct communication. Mothers supported fathering at a distance by encouraging children to keep fathers in mind, as well as providing logistical support that enabled communication. Special occasions were one area in which absences were keenly noted, and fathers could not participate in everyday decision making. Military men undertook emotion work to keep family and work separate during deployments. Discussion: The findings contribute to an understanding of how men navigate ideals of involved fathering within the constraints of work that requires frequent and sustained absences. Making presence work explicit and detailing specific techniques for creating presence can encourage military fathers to be more intentional in preparing for fathering at a distance during deployments. This, in turn, may help alleviate some tension between military and family life.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".