Overcoming Conflicting Loyalties
Bibliographic record
Abstract
To date, little has been published about the place of spirituality in working with survivors of intimate partner violence. Overcoming Conflicting Loyalties examines the intersection of faith and culture in the lives of religious and ethno-cultural women in the context of the work of FaithLink, a unique community initiative that encourages religious leaders and secular service providers to work together. The authors present the benefits of such cooperation by reporting the findings of three qualitative research studies. Individuals in secular and sacral services who work with victims of domestic violence, as well as academics in the fields of social work, psychology, and religious studies, will benefit from the insights, depth of experience, and range of voices represented in this valuable book. Irene Sevcik, Michael Rothery, Nancy Nason-Clark, and The Very Rev. Robert Pynn have brought their professional expertise and experiences to benefit FaithLink at different times and in different capacities. All of the authors live in Calgary except Nason-Clark, who lives in Fredericton. Sponsored by The Calgary Foundation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".