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Attachment, Social Rank, and Affect Regulation: Speculations on an Ethological Approach to Family Interaction<sup>*</sup>

2002· review· en· W1975035807 on OpenAlexaff
Leon Sloman, Leslie Atkinson, Karen Milligan, Giovanni Liotti

Bibliographic record

VenueFamily Process · 2002
Typereview
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsInstitute for Christian StudiesUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsAffect (linguistics)Perspective (graphical)PsychologyRank (graph theory)PsychopathologySocial relationAffect regulationAttachment theoryDevelopmental psychologySocial psychologyPsychotherapistCognitive psychologyClinical psychologyCommunicationComputer science

Abstract

fetched live from OpenAlex

The attachment and social rank systems are biological-evolutionary systems that can serve as models for conceptualizing family interaction. By exploring both their unique and interrelated impact on affect regulation, we can differentiate between processes that foster healthy growth and those leading to individual psychopathology. This perspective facilitates the integration of biological and psychological models, and has therapeutic implications. It also integrates well with other family therapy models.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.167
GPT teacher head0.477
Teacher spread0.310 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations37
Published2002
Admission routes1
Has abstractyes

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