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Record W1858888420 · doi:10.1111/josi.12068

The Emergence of Milgram's Bureaucratic Machine

2014· article· en· W1858888420 on OpenAlexaff
Nestar Russell

Bibliographic record

VenueJournal of Social Issues · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicPsychology of Social Influence
Canadian institutionsNipissing University
FundersYale UniversityNational Science Foundation
KeywordsMilgram experimentBureaucracyContext (archaeology)SociologyIdeologyObedienceSocial psychologyConformityCriminologyPsychologyPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

Based on documents from Yale University, this article advances new sociological insights on Milgram's experiments, which bolster and extend Russell and Gregory's largely psychological explanation. From behind‐the‐scenes, Milgram's experiments are viewed as an ideologically driven, inherently coercive, and goal‐orientated bureaucratic process. The individual links within this organisational chain included Milgram (project manager), Yale University (institutional support), the National Science Foundation (funding), Milgram's research team (the actors), ending with the final link, the “shock”‐inflicting participants. Analysis illustrates how the division of labour inherent within this bureaucratic process facilitated Milgram's high completion rates because when highly stressed participants inflicted the most intense shocks, every link in the chain had the opportunity to displace or diffuse personal responsibility for their actually or, for the participants, seemingly harmful contributions. This analysis is consistent with Durkheim's insistence that to better understand the behavior of individuals, the social—and therefore sociological—context must also be considered.

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 imitation

Not 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.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.040
Scholarly communication0.0060.007
Open science0.0010.005
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.022
GPT teacher head0.397
Teacher spread0.375 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations65
Published2014
Admission routes1
Has abstractyes

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