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The Trend toward more Attractive and Informative Titles: <i>American Psychologist</i> 1946–2010

2012· article· en· W2129781050 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePsychological Reports · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicAcademic Writing and Publishing
Canadian institutionsLaurentian University
Fundersnot available
KeywordsPunctuationPsychologyEmotionalityStyle (visual arts)Content (measure theory)Social psychologyLinguisticsHistoryMathematics

Abstract

fetched live from OpenAlex

Titles of journal articles serve to attract attention and inform potential readers. All titles from 65 volumes of American Psychologist (1946-2010, N = 12,313 titles) were studied in terms of their emotionality, style, and contents. Several trends noted for titles in different kinds of journals from psychology and other disciplines were present in American Psychologist (increasing title length, increasing use of punctuation marks, increasing employment of words with pleasant and arousing connotations, variations in the frequency of different content words). Longer titles allow authors to specify more information, and emotionally upbeat titles are more likely to attract reader attention. In an unexpected quadratic trend, titles became more abstract and the number of titles increased until about 1985, after which the trend was reversed and titles became more concrete as their numbers decreased. Predictors of this trend include societal variables and the journal's editorial policies.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.529
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.079
GPT teacher head0.338
Teacher spread0.259 · 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