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Record W4401192400 · doi:10.1111/pere.12567

Is teasing meant to be mean or nice? Retrospective reports of adolescent social experiences and teasing attitudes

2024· article· en· W4401192400 on OpenAlexaff
Naomi C. Z. Andrews, Oya Pakkal, Molly Dawes

Bibliographic record

VenuePersonal Relationships · 2024
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsBrock University
Fundersnot available
KeywordsNicePsychologySocial psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Abstract Peer teasing has contradictory conceptualizations, including teasing that is playful, and teasing that is akin to bullying. In addition to individuals potentially having different conceptualizations of teasing, and despite the inherently social nature of teasing, little is known about the social correlates of teasing attitudes. The current study aimed to examine multifaceted teasing attitudes (i.e., aggressive, affectionate, or romantic interest teasing), and to assess how past social experiences (victimization, popularity, social satisfaction/self‐concept) relate to teasing attitudes. Young adults ( N = 437, 17–25 years old, 65% female) reported on multifaceted teasing attitudes on a Teasing Attitudes Scale developed for this study. Participants also reported retrospectively on adolescent social experiences. Findings validated the Teasing Attitudes Scale, showing that young adults have distinct attitudes toward teasing as aggressive, affectionate, and indicating romantic interest. Participants who reported victimization by bullying, lower popularity (girls only), social satisfaction, and social self‐concept were more likely to view teasing as aggressive. Participants who had been victims of non‐bullying aggression viewed teasing as affectionate, and those with high social satisfaction and self‐concept viewed teasing as for romantic interest purposes. Implications for understanding the complexities of teasing and its associations with individual attitudes and adolescent social experiences will be discussed.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.872

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.095
GPT teacher head0.364
Teacher spread0.269 · 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 teacher head, 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

Citations6
Published2024
Admission routes1
Has abstractyes

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