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Record W2557331050 · doi:10.1521/pdps.2016.44.4.505

Borderline Personality Disorder: Therapeutic Factors

2016· article· en· W2557331050 on OpenAlexaff
Michael H. Stone

Bibliographic record

VenuePsychodynamic Psychiatry · 2016
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsColumbia College
Fundersnot available
KeywordsPsychologyPsychotherapistMentalizationBorderline personality disorderClinical psychology

Abstract

fetched live from OpenAlex

Proponents of the now half-dozen major psychotherapeutic approaches tend to claim the superiority of their different approaches-known widely by their acronyms: CBT for Cognitive Behavioral Therapy, DBT for Dialectic Behavioral Therapy, MBT for Mentalization-Based Therapy, TFP for Transference- Focused Psychotherapy, and so on. The data thus far support the utility of each method, but do not show clear-cut superiority of any one method. A large percentage of BPD patients eventually improve or even recover, but these favorable results appear to derive from a multiplicity of factors. These include the personality traits of both patient and therapist, the unpredictable life events over time, the socioeconomic and cultural background of the patient, and the placebo effect of simply being in treatment. These latter factors constitute the contextual model, which operates alongside the medical model, each playing a role in eventual outcome. The contextual model will be discussed extensively in a separate article.

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)0.006
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.018
GPT teacher head0.311
Teacher spread0.294 · 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
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

Citations9
Published2016
Admission routes1
Has abstractyes

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