Exploring the daily geographies of diverse men caregiving for family members with multiple chronic conditions
Bibliographic record
Abstract
Within Canada, it has been estimated that almost half of all family, also known as informal, caregivers are now men. However, the contributions and experiences of these caregiver men have received relatively little attention, particularly from geographies of care and caregiving researchers. This analysis hopes to shed light on the unique, yet diverse, experiences of men caregiving for persons with multiple chronic conditions in Canada. Drawing on semi-structured interviews with nineteen men caregivers in two provinces of Canada, this analysis aims to explore how social and physical axes of difference shape men’s daily lived geographies when providing care. Our thematic findings reveal that caregiving is experienced by participants at the three scalar levels of the body, the home and the community. Our intersectional analysis reveals that at each scalar level, being a man was not the only variable shaping caregiving experiences. Rather, it was also age, physical capacity, culture, socio-economic status, marital status, housing status, social connectedness, relationship to the care recipient and care recipients’ physical and mental capacity that shaped experiences and meanings of place during the caregiving process. Accounting for this diversity at each scale, our findings point to the unique stresses and challenges experienced. We conclude by emphasizing the significance in acknowledging the diverse challenges that exist for all caregivers in order to inform comprehensive and inclusive social policy that ultimately will produce equitable caregiver supports.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".