MétaCan
Menu
Back to cohort
Record W2075114479 · doi:10.1002/jhbs.20169

The social control of behavior control: Behavior modification,individual rights, and research ethics in America, 1971–1979

2006· article· en· W2075114479 on OpenAlexaff
Alexandra Rutherford

Bibliographic record

VenueJournal of the History of the Behavioral Sciences · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicOccupational and Professional Licensing Regulation
Canadian institutionsYork University
Fundersnot available
KeywordsScrutinyTerminologyCommissionPolitical scienceControl (management)Research ethicsWork (physics)Public relationsEngineering ethicsSociologyPsychologyPublic administrationLawManagementEngineering

Abstract

fetched live from OpenAlex

In 1971, the U.S. Senate Subcommittee on Constitutional Rights began a three-year study to investigate the federal funding of all research involving behavior modification. During this period, operant programs of behavior change, particularly those implemented in closed institutions, were subjected to specific scrutiny. In this article, I outline a number of scientific and social factors that led to this investigation and discuss the study itself. I show how behavioral scientists, both individually and through their professional organizations, responded to this public scrutiny by (1) self-consciously altering their terminology and techniques; (2) considering the need to more effectively police their professional turf; and (3) confronting issues of ethics and values in their work. Finally, I link this episode to the formation of the National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research, whose recommendations resulted in changes to the ethical regulation of federally funded human subjects research that persist to the present day.

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)0.014
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.043
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0010.000

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 head0.231
GPT teacher head0.385
Teacher spread0.154 · 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.

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

Citations32
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the History of the Behavioral SciencesSame topicOccupational and Professional Licensing RegulationFrench-language works237,207