Dual Relationships of Psychotherapeutically Untrained Imams Who Counsel Their Congregants: A Qualitative Study
Bibliographic record
Abstract
Abstract\nCanadian Imams, like many other religious leaders, provide counselling for members of their congregations though most of them have no formal training in psychotherapeutic counselling. The very nature of the Imams’ multiple roles in the community leads to the development of dual relationships. These dual relationships can create an ethical dilemma for Imams because they have a potential to affect the congregants positively or detrimentally. This phenomenological qualitative study explored the lived experience of 15 psychotherapeutically untrained Canadian Imams with dual relationships. Within a psychotherapeutic and an Islamic theoretical framework, this study provided a thorough analysis of five superordinate themes and 32 subthemes: Imams’ perceptions of dual relationships, positive impacts of dual relationships, negative impacts of dual relationships, types of dual relationships, and strategies for managing and coping with dual relationships. The study concluded that Imams’ professional counselling training is paramount to increasing their level of awareness of dual relationships and managing the related ethical challenges. Both psychotherapy and Islamic literature supported Imams’ views that dual relationships are inevitable due to the Imam’s multifaceted role, are not inherently harmful and could be potentially positive spiritually and therapeutically if the Imams follow certain ethical strategies to manage and avoid potential harms. This study focused on the non-sexual dual relationships of Sunni Imams hence it is recommended for future research to explore sexual dual relationships, congregants’ lived experiences with dual relationships, and Shia Imams’ dual relationships with their communities.\n@font-face {font-family:"MS Mincho"; panose-1:2 2 6 9 4 2 5 8 3 4; mso-font-alt:"ＭＳ 明朝"; mso-font-charset:128; mso-generic-font-family:modern; mso-font-pitch:fixed; mso-font-signature:-536870145 1791491579 134217746 0 131231 0;}@font-face {font-family:"Cambria Math"; panose-1:2 4 5 3 5 4 6 3 2 4; mso-font-charset:0; mso-generic-font-family:roman; mso-font-pitch:variable; mso-font-signature:-536870145 1107305727 0 0 415 0;}@font-face {font-family:Calibri; panose-1:2 15 5 2 2 2 4 3 2 4; mso-font-charset:0; mso-generic-font-family:swiss; mso-font-pitch:variable; mso-font-signature:-536859905 -1073697537 9 0 511 0;}@font-face {font-family:Cambria; panose-1:2 4 5 3 5 4 6 3 2 4; mso-font-charset:0; mso-generic-font-family:roman; 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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".