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Record W2128617501

Borderline Pathology of Childhood: Implications of Early Axis II Diagnoses.

2004· article· en· W2128617501 on OpenAlexaffabout
Phyllis Zelkowitz, Jaswant Guzder, Joel Paris, Ron Feldman, Carmella Roy, Alessandra Schiavetto

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsPersonality pathologyPsychopathologyClinical psychologyPsychologyNeuropsychologyMedical diagnosisIntervention (counseling)PersonalityPsychiatryBorderline personality disorderPersonality disordersDevelopmental psychologyMedicineCognitionPathology
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: A personality pathology framework may be useful in the diagnosis and treatment of children with chronic psychopathology and impairment in many domains of functioning. This paper presents the utility of such an approach through a description of research investigating borderline pathology of childhood (BPC). METHODS: Literature regarding the phenomenology, risk factors, and outcomes of BPC and similar disorders is reviewed. RESULTS: Research conducted at the SMBD-Jewish General Hospital in Montreal has shown that children with BPC can be reliably identified via chart review, and that they exhibit a pattern of risk factors similar to that of adults with borderline personality disorder, such as psychological trauma and deficits in executive function. Preliminary results of a follow-up study in adolescence suggests that these children remain more functionally impaired than a comparison group. Our current research investigates neuropsychological deficits and their relationship to trauma in children with BPC. We are also exploring whether a similar pattern can be observed in their parents. CONCLUSION: We conclude that BPC symptom patterns may diagnostically define a group of high risk children and may eventually guide our approach to early intervention.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.623
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.023
GPT teacher head0.285
Teacher spread0.262 · 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

Citations11
Published2004
Admission routes2
Has abstractyes

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