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Record W2892173855 · doi:10.1177/0963721418767873

The Parental Care Motivational System and Why It Matters (for Everyone)

2018· article· en· W2892173855 on OpenAlexafffund
Mark Schaller

Bibliographic record

VenueCurrent Directions in Psychological Science · 2018
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologySocial psychologyAggressionPerceptionPrejudice (legal term)Paternal careImpression formationDevelopmental psychologySocial perception

Abstract

fetched live from OpenAlex

Although it is easy to assume that the psychology of parental care pertains only to parents and their children, this is not so. An emerging body of research on the parental care motivational system reveals implications for everyone. All normally developing human beings are characterized by evolved psychological mechanisms that regulate parental caregiving. These mechanisms are responsive to superficial cues and so (among nonparents as well as parents) can be triggered by the perception of young children or other childlike things. Once activated, these mechanisms precipitate protective and nurturant responses. These responses manifest in many different ways, with implications for a wide range of psychological phenomena (many of which might appear, superficially, to be unrelated to caregiving)—including risk-averse attitudes, aggression, intergroup prejudice, moral judgment, impression formation, and mate preferences. This article provides an illustrative overview of empirical research documenting these implications and identifies new directions for future research on the motivational psychology of parental care.

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)0.004
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.073
GPT teacher head0.426
Teacher spread0.352 · 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

Citations74
Published2018
Admission routes2
Has abstractyes

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