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Record W1971832906 · doi:10.1080/00223891.2011.594127

Use of the Adult Attachment Projective Picture System in an Assessment of an Adolescent in Foster Care

2011· article· en· W1971832906 on OpenAlexaff
Linda Webster, David Joubert

Bibliographic record

VenueJournal of Personality Assessment · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsConceptualizationPsychologyProjective testJuvenile delinquencyDevelopmental psychologyProjective identificationSet (abstract data type)Foster carePsychoanalysisPsychoanalytic theoryArtificial intelligence

Abstract

fetched live from OpenAlex

Child maltreatment has been associated with a host of negative outcomes including impaired social relationships (Rogosch, Cicchetti, & Aber, 1995), depression (Toth, Manly, & Cicchetti, 1992), poor self-concept and motivation (Vondra, Barnett, & Cicchetti, 1990), and delinquency and conduct problems (Cook et al., 2005; Grotevant et al., 2006; McCabe, Lucchini, Hough, Yeh, & Hazen, 2005; Ryan & Testa, 2005). An assessment of the mental representation of attachment relationships could offer additional relevant and useful information to the evaluation of youth in foster care, and could inform treatment and placement considerations. The Adult Attachment Projective Picture System (AAP) is a relatively new measure of internal representations of attachment based on the analysis of a set of stimuli designed to systematically activate the attachment system (George, West, & Pettem, 1997). This article considers the use of the AAP with a maltreated adolescent in a clinical setting and uses a case study to illustrate the components of the AAP that are particularly relevant to case conceptualization and interventions.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.048
Threshold uncertainty score0.745

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.080
GPT teacher head0.396
Teacher spread0.316 · 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
Published2011
Admission routes1
Has abstractyes

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