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Record W2329170809 · doi:10.1017/s0140525x13003348

The perils of a science of intentional change

2014· letter· en· W2329170809 on OpenAlexaff
Muhammad Ali Khalidi

Bibliographic record

VenueBehavioral and Brain Sciences · 2014
Typeletter
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsYork University
Fundersnot available
KeywordsConstruct (python library)Action (physics)Reliability (semiconductor)PsychologySocial psychologySociologyEngineering ethicsEpistemologyComputer scienceEngineeringPhilosophy

Abstract

fetched live from OpenAlex

The attempt to construct an applied science of social change raises certain concerns, both theoretical and ethical. The theoretical concerns relate to the feasibility of predicting human behavior with sufficient reliability to ground a science that aspires to the management of social processes. The ethical concerns relate to the moral hazards involved in the modification of human social arrangements, given the unreliability of predicting human action.

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)0.049
metaresearch head score (Gemma)0.127
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.051
Threshold uncertainty score0.261

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0490.127
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.001
Science and technology studies0.0070.082
Scholarly communication0.0100.024
Open science0.0050.009
Research integrity0.0510.116
Insufficient payload (model declined to judge)0.0060.005

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 head0.324
GPT teacher head0.445
Teacher spread0.121 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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
Published2014
Admission routes1
Has abstractyes

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