Stanley Milgram’s Obedience to Authority “Relationship” Condition: Some Methodological and Theoretical Implications
Bibliographic record
Abstract
In May 1962, social psychologist, Stanley Milgram, ran what was arguably the most controversial variation of his Obedience to Authority (OTA) experiments: the Relationship Condition (RC). In the RC, participants were required to bring a friend, with one becoming the teacher and the other the learner. The learners were covertly informed that the experiment was actually exploring whether their friend would obey an experimenter’s orders to hurt them. Learners were quickly trained in how to react to the impending “shocks”. Only 15 percent of teachers completed the RC. In an article published in 1965, Milgram discussed most of the variations on his baseline experiment, but only named the RC in passing, promising a more detailed account in his forthcoming book. However, his 1974 book failed to mention the RC and it remained unpublished until François Rochat and Andre Modigliani discovered it in Milgram’s personal archive in 1997 at Yale University. Their overview of the RC’s procedure and results left a number of questions unanswered. For example, what were the etiological origins of the RC? Why did Milgram decide against publishing this experiment? And does the RC have any significant methodological or theoretical implications on the Obedience studies discourse? Based on documents obtained from Milgram’s personal archive, the aim of this article is to shed new light on these questions.
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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 | 0.050 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| 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".