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Record W1989052401 · doi:10.1177/019027250606900302

Ambivalence in Mother-Adult Child Relations: A Dyadic Analysis

2006· article· en· W1989052401 on OpenAlexaff
Andrea E. Willson, Kim M. Shuey, Glen H. Elder, K. A. S. Wickrama

Bibliographic record

VenueSocial Psychology Quarterly · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsWestern University
Fundersnot available
KeywordsAmbivalencePsychologyInterpersonal relationshipDevelopmental psychologySocial psychologySocial relationInterpersonal communicationInterpersonal interactionSocial relationship

Abstract

fetched live from OpenAlex

The concept of ambivalence represents an interactional process in which individuals evaluate social relations as simultaneously positive and negative. This study investigates ambivalence in interpersonal relations through an empirical analysis of relationships between aging mothers and their adult children from their joint perspectives. Multilevel models examine the influence of dependence on levels of ambivalence in relationship dyads as well as differences in levels of ambivalence between mothers and their adult children. Results suggest that ambivalence increases under conditions of potential dependence, rather than through the help that is more routinely exchanged among family members. Within the relationship, mothers experienced less ambivalence than their sons and daughters; overall findings demonstrate the importance of analyzing multiple perspectives in social relationships.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.003
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 head0.008
GPT teacher head0.313
Teacher spread0.305 · 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 designQualitative
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

Citations98
Published2006
Admission routes1
Has abstractyes

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