Love and Resistance: Moral Solidarity in the Face of Perceptual Failure
Bibliographic record
Abstract
In this paper I explore how we ought to respond to the problematic inner lives of those that we love. I argue for an understanding of love that is radical and challenging—a powerful form of resistance within the confines of everyday relationships. I argue that love, far from the platitudinous and saccharine view, does not call for our acceptance of others’ failings. Instead, loving another means believing in their potential to grow and holding them to account when they fail. I argue that loving others means meeting them where they are and working to understand the role that oppressive ideologies, coupled with cognitive biases, play in generating and entrenching their problematic mental states. I then argue that we ought not disengage with our loved ones or write them off as lost causes, nor should we accept that we will simply “agree to disagree.” Instead, we should stand in moral solidarity with our loved ones and press them to become better while simultaneously understanding that such moral growth is usually a slow and painful process—often, the project of a lifetime.
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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.033 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".