Why Moral Psychology is Disturbing: Regina Rini
Bibliographic record
Abstract
Overview & Shownotes Regina Rini holds the Canada Research Chair in Philosophy of Moral and Social Cognition at York University. She joins us today to discuss why we might be disturbed when we learn about the role that psychology plays in our moral decision-making. For the episode transcript, download a copy or read it below. Contact us at examiningethics@gmail.com Links to people and ideas mentioned in the show “Why moral psychology is disturbing” by Regina Rini Philosopher-neuroscientist Joshua Greene Deontology Consequentialist ethics Kantian theory The trolley problem Radiolab episode mentioned in the discussion Robert Sapolsky Aristotle’s ethics Nicomachean ethics Bernard Williams Charles Stevenson Friedrich Nietzsche Christine Korsgaard and her thoughts on agency Nic Bommarito Case developed by a philosopher Nomy Arpaly Credits Thanks to Evelyn Brosius for our logo. Music featured in the show: “Coulis Coulis” by Blue Dot Sessions
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".