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Record W2325328801 · doi:10.1177/0963721415626678

Oxytocin and the Pharmacological Dissection of Affiliation

2016· article· en· W2325328801 on OpenAlexafffund
Jennifer A. Bartz

Bibliographic record

VenueCurrent Directions in Psychological Science · 2016
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsMcGill University
FundersNational Institute of Child Health and Human DevelopmentNatural Sciences and Engineering Research Council of CanadaNational Institutes of Health
KeywordsOxytocinPsychologySocial cognitionSalience (neuroscience)AnxietyDevelopmental psychologyCognitionSocial anxietyCognitive psychologySocial psychologyNeuroscience

Abstract

fetched live from OpenAlex

Popularly hailed as the “love hormone,” oxytocin has emerged as a key variable in the regulation of human social cognition and behavior. In particular, research using intranasal oxytocin to pharmacologically manipulate the availability of oxytocin shows that oxytocin augmentation can promote a wide range of affiliative processes; however, evidence also shows null and even antisocial effects. Rather than random error to be eliminated, such variability may offer clues about the mechanisms by which oxytocin modulates human sociality. Three potential mechanisms—anxiety reduction, social salience, and affiliative motivation—are discussed, along with recent work showing how the affiliative-motivation hypothesis can simultaneously account for oxytocin’s pro- and antisocial effects. Appreciating oxytocin’s nuanced social effects is important for advancing our understanding of the neuroscience and psychology of affiliation.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.069
GPT teacher head0.473
Teacher spread0.404 · 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 designTheoretical or conceptual
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

Citations78
Published2016
Admission routes2
Has abstractyes

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