Obedience with Pauline Shanks Kaurin
Bibliographic record
Abstract
Overview & Shownotes There’s perhaps no better example of an obedient person than a soldier. And yet, soldiers often thoughtfully disobey direct orders, and in some cases, are legally obligated to disobey the rules. Pauline Shanks Kaurin, who is a philosopher and professor of military ethics at the U.S. Naval War College joins us to explore the ethics of obedience. She’s discussing her book On Obedience: Contrasting Philosophies for the Military, Citizenry, and Community. 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 Pauline Shanks Kaurin, On Obedience: Contrasting Philosophies for the Military, Citizenry, and Community Mỹ Lai massacre Hugh Thompson Alasdair MacIntyre, After Virtue Martin Luther King, Jr., “Letter from a Birmingham Jail“ Thomas Aquinas on unjust laws USS Theodore Roosevelt and COVID-19 Credits Thanks to Evelyn Brosius for our logo. Music featured in the show: “Gin Boheme” by Blue Dot Sessions “Calgary Sweeps” by Blue Dot Sessions
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".