Being a father in the military: an exploration of six Canadian veterans' subjective experiences.
Bibliographic record
Abstract
This study used a qualitative approach to explore the experiences of six veterans, who were employed by the military and who were fathers at the time of their military employment. Semi-structured interviews with participants were used as the primary method of data collection. The researcher asked participants, “What do I need to know to understand what it is like to be a father in the military?” Additional probing questions were used to clarify and expand on the participants’ experiences of bonding emotionally with their children as a father in the military, as well the participants’ experiences of separating from their family and subsequently reuniting following military deployments and occupational travel. Using thematic analysis, the researcher constructed the following themes: (1) “You miss out” (2) “You feel like and outsider” (3) “You try to disconnect from family to deal with work” and (4) “The military comes first.” The current research adds to our understanding of the subjective experience of fatherhood in the military. The themes extracted will be helpful in delineating valuable counselling strategies for fathers in the military, as well as developing military policies and practice that support these fathers in their contribution to the healthy development of their children.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".