Difficult male clients? Social service and health practitioners’ perspectives
Bibliographic record
Abstract
Men continue to underutilize health and social services, often presenting late, in distress, and with behaviors that clash with dominant therapeutic models. This study explores how service providers interpret and navigate these challenges, drawing on critical incident interviews with 47 practitioners across the social and health sectors in Québec, conducted during the initial phase of a larger study evaluating a professional development program. Practitioners reported recurring difficulties engaging men, including resistance to introspection, emotional withdrawal, and perceived aggression. Rather than pathologizing these behaviors, we interpret them through Raymond Boudon’s theory of actor rationality and his concept of Homo sociologicus —which positions individuals as acting according to socially situated reasoning within their cultural and social contexts. We argue that service providers often misread men’s help-seeking behaviors due to conflicting social logics shaped by gender norms. To bridge this gap, we propose integrating Homo sociologicus into practitioner training, encouraging epistemological breaks from normative assumptions, and promoting action-oriented, reflexive intervention models. By reframing men’s behaviors as socially meaningful rather than resistant, practitioners can improve relational engagement, tailor services more effectively, and reduce structural barriers to care.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.028 | 0.023 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".