Martin Buber: guide for a psychology of suffering
Bibliographic record
Abstract
Martin Buber was untrained in psychology, yet his teaching provides helpful guidance for a psychological science of suffering. His ideas deserve attention at three distinct levels. For each of these, his ideas align with research findings, but also push beyond them. At the individual level, Buber's radical approach to relationships disrupts typical social cognitive cycles of suffering and can thereby build a defense against suffering. At the community level, he provides guidance that can help create a society that cares for people who suffer. At the dyadic level, Buber's guidance also matters. His ideas point toward a therapeutic dyad that can help address suffering when the individual and community responses are not sufficient. Specifically, he guides us toward a holistic view of the person that transcends labels and also toward ineffable human relations. Here again, his ideas align with empirical research, but push beyond. Buber's unique take on relationships has much to offer scholars seeking to understand and alleviate suffering. Some might perceive Buber as ignoring evil. That possible criticism and others deserve consideration. Nonetheless, readiness to adjust theory in response to Buber and other psychological outsiders may be valuable when developing a psychology of suffering.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.027 | 0.032 |
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".