Bibliographic record
Abstract
Acceptance and Commitment Therapy (ACT) is a psychological intervention that has wide clinical applications with emerging empirical support. It is based on Functional Contextualism and is derived as a clinical application of the Relational Frame Theory, a behavioral account of the development of human thought and cognition. The six core ACT therapeutic processes include: Acceptance, Defusion, Present Moment, Self-as-Context, Values, and Committed Action. In addition to its explicit use of the concept of mindfulness, the therapeutic techniques of ACT implicitly incorporate other aspects of Buddhism. This article describes the basic principles and processes of ACT, explores the similarities and differences between ACT processes and some of the common tenets in Buddhism such as the Four Noble Truths and No-Self, and reports on the experience of running a pilot intervention ACT group for the Cambodian community in Toronto in partnership with the community's Buddhist Holy Monk. Based on this preliminary exploration in theory and the reflections of the group experience, ACT appears to be consistent with some of the core tenets of Buddhism in the approach towards alleviating suffering, with notable differences in scope reflecting their different aims and objectives. Further development of integrative therapies that can incorporate psychological and spiritual as well as diverse cultural perspectives may help the continued advancement and evolution of more effective psychotherapies that can benefit diverse populations.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".