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Record W2268130350 · doi:10.1080/1357650x.2015.1136320

Family matters: Directionality of turning bias while kissing is modulated by context

2016· article· en· W2268130350 on OpenAlexafffund
Jennifer R. Sedgewick, Lorin Elias

Bibliographic record

VenueLaterality Asymmetries of Body Brain and Cognition · 2016
Typearticle
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaJohns Hopkins University
KeywordsKISS (TNC)Context (archaeology)RomancePsychologySituational ethicsDevelopmental psychologySocial psychologyGeographyPsychoanalysisComputer science

Abstract

fetched live from OpenAlex

When leaning forward to kiss to a romantic partner, individuals tend to direct their kiss to the right more often than the left. Studies have consistently demonstrated this kissing asymmetry, although other factors known to influence lateral biases, such as sex or situational context, had yet to be explored. The primary purpose of our study was to investigate if turning direction was consistent between a romantic (parent-parent) and parental (parent-child) kissing context, and secondly, to examine if sex differences influenced turning bias between parent-child kissing partners. An archival analysis coded the direction of turning bias for 161 images of romantic kissing (mothers kissing fathers) and 529 images of parental kissing (mothers or fathers kissing sons or daughters). The results indicated that the direction of turning bias differed between kissing contexts. As expected, a right-turn bias was observed for romantic kissing; however, a left-turn bias was exhibited for parental kissing. There was no significant difference of turning bias between any parent-child kissing partners. Interpretations for the left-turn bias discuss parental kissing as a learned lateral behaviour.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.045
GPT teacher head0.267
Teacher spread0.222 · 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 designBench or experimental
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

Citations21
Published2016
Admission routes2
Has abstractyes

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