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Record W2747289385 · doi:10.5539/ijps.v9n3p92

Expectations of Male and Female Adoptive Parents of Different Marital Status and Sexual Orientation

2017· article· en· W2747289385 on OpenAlexvenueno aff
Sara L. Sohr‐Preston, Holly Kliebert, Olivia Moreno, Timothy Dugas, Dylan Zepeda

Bibliographic record

VenueInternational Journal of Psychological Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyImmoralityDevelopmental psychologyProspective cohort studyWifePreferenceAnticipation (artificial intelligence)Social psychology

Abstract

fetched live from OpenAlex

Adults in the U.S. (undergraduate college students and adults recruited online) read vignettes about a fictional individual seeking to adopt an infant. Based on random assignment, participants read versions in which the prospective adoptive parent described was either an implied male or female and single, married to someone of the opposite sex, or married to someone of the same sex. After reading the vignettes, participants rated their expectations of the prospective parent’s ability to parent and their perceptions of the prospective parent’s personal characteristics. Female participants reported significantly (p < .05) higher expectations of general ability to parent and perceived higher responsibility, greater likeability, and less selfishness. Both sexes endorsed significantly lower anticipation of ability to parent and less responsibility when the prospective parent was designated as single or in a same-sex marriage. Same-sex prospective parents were additionally rated as significantly higher in immorality. Prospective fathers were rated as less likeable than prospective mothers and participants approved less of their plan to adopt. The authors discuss findings as relevant to bias favoring traditional families headed by a man and a woman with the wife taking the lead in the transition to parenthood.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.034
Threshold uncertainty score0.232

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.123
GPT teacher head0.447
Teacher spread0.324 · 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

Citations8
Published2017
Admission routes1
Has abstractyes

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