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Record W2811270367 · doi:10.4236/psych.2018.96092

Characterological Correlates of Selfie Taking Behavior

2018· article· en· W2811270367 on OpenAlexafffund
Eric D Gilliland, Mark Kiss, Melanie A. Morrison, Todd G. Morrison

Bibliographic record

VenuePsychology · 2018
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsUniversity of Saskatchewan
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSelfiePsychologyNeuroticismSocial mediaShameBig Five personality traitsSocial psychologyPersonalityWorld Wide Web

Abstract

fetched live from OpenAlex

Few researchers have examined selfie taking behavior. To address this gap, 235 participants (age 18 - 60) completed an online questionnaire assessing a variety of psychological factors, personality traits, and selfie taking activities (i.e., frequency of selfies posted to social networking sites [SNSs], time spent editing selfies, and number of selfie takes prior to posting). A number of statistically significant correlations emerged. For example, participants’ levels of neuroticism, social physique anxiety, body-related shame, and concern about physical appearance correlated positively with the amount of time spent editing selfies. As well, group comparisons between selfie (n = 193) and non-selfie takers (n = 42) suggest that the former exhibit higher levels of certain facets of vanity. The implications of these findings and directions for future research are outlined.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.102
GPT teacher head0.427
Teacher spread0.325 · 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

Citations7
Published2018
Admission routes2
Has abstractyes

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