The Uses of Hopelessness: A Response to Røkenes and Jornet
Bibliographic record
Abstract
ABSTRACT In this response to Røkenes and Jornet as part of the special issue Centering Affect and Emotion Toward Justice and Dignity in Science Education , we celebrate the contributions they make as they analyze Norwegian teenagers grappling with hope and hopelessness as part of a disciplinary unit on environmental sustainability. We discuss various ways of treating hope and hopelessness as emotional configurations and sensemaking tools. We draw on alternate theorizations of hope, including hope as a discipline, active hope, and critical hope, to argue for politicized understandings of hopelessness as an often‐necessary part of climate education. We argue that if hope is a learning target for science education, critical science educators must teach and practice social movement repertoires that build power, giving young people a taste of meaningful social action and embedding them in politicized relations of solidarity.
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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 | 0.037 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.056 |
| Scholarly communication | 0.011 | 0.018 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.030 | 0.081 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".