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Record W2159294915 · doi:10.1002/per.655

Personality characteristics of research volunteers

2007· article· en· W2159294915 on OpenAlexafffund
Jan‐Erik Lönnqvist, Sampo V. Paunonen, Markku Verkasalo, Sointu Leikas, Annamari Tuulio‐Henriksson, Jouko Lönnqvist

Bibliographic record

VenueEuropean Journal of Personality · 2007
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsWestern University
FundersSocial Sciences and Humanities Research Council of CanadaAcademy of Finland
KeywordsAgreeablenessConscientiousnessPsychologyPersonalityExtraversion and introversionNeuroticismBig Five personality traitsClinical psychologyHierarchical structure of the Big FiveSiblingSocial psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

We evaluated Big Five personality factor differences between research volunteers and nonvolunteers. In the first study, 158 military officers were asked to participate in a mail survey. The personality scores of the officers were available from an archival data set. In our second study, adult siblings from large families were invited to participate in extensive clinical epidemiological evaluations. The personality scores of volunteers (N = 55) and nonvolunteers from the same families (N = 29) were estimated from sibling ratings made by those who participated in the study. In both studies, respondents, compared to nonrespondents, were found to be significantly lower in Neuroticism and higher in Conscientiousness. The second study further indicated respondents as being higher in Extraversion and Agreeableness. Copyright © 2007 John Wiley & Sons, Ltd.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.135
GPT teacher head0.428
Teacher spread0.293 · 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 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

Citations77
Published2007
Admission routes2
Has abstractyes

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