Religion and spirituality as a core module in social work education in Nigeria: perspectives of social work educators
Bibliographic record
Abstract
Religion and spirituality are central to everyday life in Nigeria. Social work educators recognize that learning cannot be separated from the influence of context, including religion and spirituality. This study presents the first empirical inquiry into religion and spirituality in social work education in Nigeria. The qualitative study explored the inclusion of religion and spirituality on Nigerian social work programs from the viewpoints of social work educators, adopting a phenomenological approach. Data from key informants’ semi-structured interviews with 12 purposively sampled social work educators based at three Nigerian universities (University of Nigeria, Nsukka; University of Benin, and Nnamdi Azikiwe University) were analyzed thematically. The findings highlight the importance of religion and spirituality in social work education; yet point to coverage being limited and located within elective modules, and for social work educators to recognize the relevance of religious and spiritual aspects of their students’ and service users’ existence in developing educational curricula. The study calls for prioritizing the integration of religion and spirituality in social work degree programs. Strengthening the links between religion, spirituality, and social work will better prepare future practitioners to be cultural component and work with the profession’s values of social justice.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.004 |
| 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".