Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The evidence is overwhelming that members of particularly wealthy and industry-owning segments of Western societies have much larger carbon footprints than most other humans, and thereby contribute far more than their “fair share” to the enormous problem of climate change. Nonetheless, in this paper we shall counsel against a strategy focused primarily on blaming and shaming and propose, instead, a change in the ethical conversation about climate change. We recommend a shift in the ethical framework from a focus on the role of individual agents and a conversation about guilt; in its place, we propose a relational approach to public health ethics that is centered around the idea of relational solidarity. We begin by briefly reviewing the most common—and woefully inadequate—approach in the West to reducing emissions and responding to the health-related impacts of climate change. We then go on to propose a relational approach to public health ethics as an alternative ethical framework that better fits the moral problems associated with climate change and holds promise for a more meaningful response.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 it