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Record W2527586762 · doi:10.1037/a0038406

Searching for the structure of early American psychology: Networking Psychological Review, 1894–1908.

2015· article· en· W2527586762 on OpenAlexfundno aff
Christopher D. Green, Ingo Feinerer, Jeremy Trevelyan Burman

Bibliographic record

VenueHistory of Psychology · 2015
Typearticle
Languageen
FieldPsychology
TopicAcademic and Historical Perspectives in Psychology
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsConsciousnessPeriod (music)PsychologySociologySocial sciencePsychoanalysisEpistemologyPhilosophyAesthetics

Abstract

fetched live from OpenAlex

This study investigated the intellectual structure of early American psychology by generating 3 networks that collectively included every substantive article published in Psychological Review during the 15-year period from the journal's start in 1894 until 1908. The networks were laid out so that articles with strongly correlated vocabularies were positioned close to each other spatially. Then, we identified distinct research communities by locating and interpreting article clusters within the networks. We found that, from the first 5-year time block to the second, psychological specialties rapidly differentiated themselves from each other. Between the second and third 5-year time blocks, however, the number of specialties shrunk. We discuss the degree to which this shift may have been attributable either to a change in the journal's editorship in 1904, or to a broader crisis of confidence, beginning that same year, in the use of "consciousness" as the discipline's defining concept.

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)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.006
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.131
GPT teacher head0.448
Teacher spread0.317 · 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 designNot applicable
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

Citations36
Published2015
Admission routes1
Has abstractyes

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