Hope Theory: A Framework for Understanding Suicidal Action
Bibliographic record
Abstract
This article examines C. R. Snyder's (1994 Snyder , C. R. ( 1994 ). The psychology of hope: You can get there from here . New York : Free Press . [Google Scholar] 2000a Snyder , C. R. ( 2000a ). Handbook of hope: Theory, measures, and applications . San Diego : Academic Press .[Crossref] , [Google Scholar]) theory of hope and its application for understanding suicide. Strengths, weaknesses, and gaps in the suicide literature are outlined, and A. T. Beck's theory of hopelessness is compared with Snyder's hope theory. Hope theory constructs are used to examine the relationship of suicide to hope/hopelessness, goals, pathways thinking, and agency thinking. This critical review is intended to broaden our theoretical understanding of suicide and is meant to form the basis for future empirical investigation of suicide-related behavior using the framework of hope theory. Implications for suicide prevention programs and approaches to treating suicidal individuals are outlined.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".