Bibliographic record
Abstract
Abstract This book explores the nature, value, and role of hope in human life under conditions of oppression. Oppression is often a threat and damage to hope, yet many members of oppressed groups, including prominent activists pursuing a more just world, find hope valuable and even essential to their personal and political lives. This book offers a unique evaluative framework for hope that captures the intrinsic value of hope for many of us, the rationality and morality of hope, and ultimately how we can hope well in the non-ideal world we share. It develops an account of the relationship between hope and anger about oppression and argues that anger tends to be accompanied by hopes for repair. When people’s hopes for repair are not realized, as is often the case for those who are oppressed, anger can evolve into bitterness: a form of unresolved anger involving a loss of hope that injustice will be sufficiently acknowledged and addressed. But even when all hope might seem lost or out of reach, faith can enable resilience in the face of oppression. Spiritual faith, faith in humanity, and moral faith are part of what motivates people to join in solidarity against injustice, through which hope can be recovered collectively. Joining with others who share one’s experiences or commitments for a better world and uniting with them in collective action can restore and strengthen hope for the future when hope might otherwise be lost.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".