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
As a vegetarian for several decades, Sue Hendler had a criterion for what could and could not be consumed: “Never eat anything that has a face.” Indeed, she once chided me, on those grounds, for eating shrimps. Her criterion exemplifies two important aspects of ethical decision-making. First, what ought to be done or not done depends upon what entities one is dealing with and deciding about. In other words, good ethics depends upon sound metaphysics; moral decision-making is, in part, a function of one’s ontology. Second, what something is (its ontology) to us as human beings—for example, a “being with a face”—partly depends upon how we relate to it, because how we relate to something makes some of its characteristics more salient than others, and even (in some cases) creates those characteristics. In other words, ontological identity is, in part, relational, and relating and relationships are core contributors to good ethical reasoning. This paper explores and elaborates upon these two fundamental claims, and shows how Sue Hendler supported these ideas in her life and in her work as a feminist planner.
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 | 0.024 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it