Bibliographic record
Abstract
Catholic psychotherapy is a critically important specialization that underscores the need for culturally competent best practices. It integrates state-of-the-art psychotherapeutic professional services with the rich religious, spiritual, and cultural contributions and traditions of the Roman Catholic Church. Since the Church is the single largest religious denomination in the world and represents about a quarter of the United States population, there is ample need for Catholic-informed and engaged psychotherapists with expertise in working thoughtfully and sensitively with Catholic clients, including laypersons and clerics, and with Church institutions such as schools, hospitals, and charitable groups. While the Catholic Psychotherapy Association has been an important organization to promote Catholic psychotherapy, a new journal dedicated to this topic provides a mechanism to share quality peer-reviewed science, practice, and reflection on how to move the field forward in a way that serves the most people possible. This article reflects on two central questions: What is Catholic psychotherapy, and who are good candidates to provide and receive these specialized services? It also offers examples of cases that fit well into the Catholic psychotherapy approach, and it discusses future directions as well as potential ethical challenges.
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 | 0.023 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.024 |
| Scholarly communication | 0.011 | 0.018 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.013 | 0.025 |
| Insufficient payload (model declined to judge) | 0.004 | 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".