What the rule of law should mean in civics education: from the ‘Following Orders’ defence to the classroom
Bibliographic record
Abstract
Sixty years after the International Military Tribunal opened in Nuremberg to try ‘major war criminals’, how should soldiers learn not to follow clearly illegal or unconscionable orders? Following the Charter of the International Military Tribunal, judges during the Nuremberg Trials rejected defendants' efforts to avoid punishment on the basis of superior orders. The Cold War stymied subsequent efforts to codify the norm; subsequent tribunals have adopted similar, but not identical, versions of the rule, as have domestic legal systems. Psychological research by Lawrence Kohlberg and Stanley Milgram raises serious questions about whether young soldiers can or will use their own moral assessments to disobey illegal orders or resist engagement in conduct abusing the rights of others. Further adding to the risks of atrocity are the stress and fear of wartime, the ambiguities and complexities of the war against terror, and confusion about the actual standards governing detentions, interrogations and treatment of civilians by the military. Hence, reducing the risks of atrocity requires not only refining and teaching the rule that superior orders are not a defence to military atrocity but also integrating legal and ethical analysis into the day‐to‐day operations of the military, and conceiving of law in this context as a constant set of questions. The dilemma posed for the soldier who must learn both to obey orders and to resist illegal orders offers a rich focal point for students in middle and high school settings. Such instruction could strengthen civilian oversight of the military while also deepening students' abilities to bring their conscience to bear in many settings where obedience and conformity jeopardize adherence to law and morality. This is the text of the 18th Lawrence Kohlberg Memorial Lecture presented at the 31st annual conference of the Association for Moral Education and the Facing History and Ourselves/Harvard Facing History Conference, Harvard University, Cambridge, MA, 4 November 2005.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.018 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.010 | 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".