Psychology’s Potential for Reconciliation with Spiritual and Religious Traditions
Bibliographic record
Abstract
In exploring psychology’s relationship with spirituality and religion, I argue that natural-science psychologists have tended to repress their discipline’s spiritual and religious heritage. History of psychology textbooks sharply distinguish “objective” psychology from “subjective” philosophy, theology, religion, and spirituality, while glossing over historical anomalies such as natural-science psychologists’ ambivalent stance regarding psychoanalysis. Psychologists’ scientism (“worship” of the experimental model, technology, scientific progress, and materialist conceptions of the soul) militates against resolving persistent, disciplinary tensions between objectivity and subjectivity. Rather than emulating psychology, social workers should turn to their own traditions and develop a human-science orientation for their profession. When theorizing, they could connect empowerment and the ecological metaphor with these concepts’ spiritual base. When researching, social workers could foster more active roles for their participants and could write their research articles in more personalized, inter-subjective, and contextualized ways. When educating, they could incorporate critical education in process and content.
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 | 0.016 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.075 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.004 | 0.008 |
| 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".