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Record W2948038958 · doi:10.3390/socsci8060178

Climate Catastrophe and Stanley Milgram’s Electric Shock “Obedience” Experiments: An Uncanny Analogy

2019· article· en· W2948038958 on OpenAlexaff
Nestar Russell, Annette Bolton

Bibliographic record

VenueSocial Sciences · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPsychology of Social Influence
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsObedienceMilgram experimentImpunitySuspectSocial psychologyBureaucracyPsychologySociologyLawEnvironmental ethicsCriminologyPolitical sciencePoliticsPhilosophy

Abstract

fetched live from OpenAlex

Awareness of impending climate catastrophe has greatly increased over the last 30 years. Increasing awareness, however, has not translated into decreasing but instead increasing greenhouse gas emissions. This paper aims to shed new light on this perplexing and ultimately destructive positive correlation. It does so by applying a new interpretation of Milgram’s Obedience to Authority “electric shock” experiments to the problem of climate catastrophe. This paper reveals that both the Obedience Studies and climate catastrophe share a crucial common denominator: both involve powerful figures utilising manipulative techniques of bureaucratic organisation to push and pull the functionary helpers below them into contributing to preconceived goal achievement. In both cases, for the functionary helpers to achieve the goals of the powerful, all must agree to contribute to the infliction of harm on a powerless group. Nearly all helpers choose to make their harmful contributions because they not only stand to personally benefit, they also suspect that—with so many other links in the chain participating in goal achievement—they can probably do so with total impunity. It is argued that this comparison may help to better understand the complex, self-reinforcing, yet ultimately destructive relationship shared between fossil fuel corporations, the ideological pursuit of economic growth, political impotence, rapacious consumer demand, and impending climate catastrophe.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.003
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.404
Teacher spread0.359 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations2
Published2019
Admission routes1
Has abstractyes

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