Bibliographic record
Abstract
Abstract Equanimity is an important concept in the relationship between Buddhist tradition and contemporary mental healthcare. In both practices, equanimity matters deeply, so it represents a useful point of interaction between Buddhism and psychiatry. In the history of medicine, equanimity has been emphasised by such figures as Irish asylum doctor James Duncan (1812–1895) and Canadian physician Sir William Osler (1849–1919). Recent decades have seen a remarkable growth in literature linking various aspects of Buddhism with psychiatric care, as well as cross-cultural conceptualisations of equanimity and emotional equilibrium. Links with Buddhist thought include the ‘Four Immeasurables’ or brahmavihārā of Buddhist tradition, which are loving-kindness (mettā), compassion (karuṇā), empathetic joy (muditā), and equanimity (upekkhā). This chapter discusses the resonances between Buddhism and psychiatry in this context, along with the limits of equanimity and the need for other values to complement it. The chapter concludes by presenting evidence of the benefits of cultivating equanimity in the general population and among health professionals, along with practical ways to deepen equanimity, especially in psychiatry but also more broadly. These approaches focus on five key themes: (a) emotional awareness; (b) mindfulness; (c) reflective practices; (d) self-compassion and self-care; (e) anchoring in professional purpose.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| 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".