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Record W2090701681 · doi:10.1037/a0015749

Symptom specificity and the prospective generation of life events in adolescence.

2009· article· en· W2090701681 on OpenAlexaff
Kate L. Harkness, Jeremy G. Stewart

Bibliographic record

VenueJournal of Abnormal Psychology · 2009
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsQueen's University
Fundersnot available
KeywordsPsychologyContext (archaeology)Depression (economics)Beck Depression InventoryClinical psychologyDevelopmental psychologyCognitionPsychiatryAnxiety

Abstract

fetched live from OpenAlex

The purpose of the present study was to uncover patterns in the generation of life events from symptom profiles and specific depression symptoms in an effort to obtain a fine-grained understanding of the stress-generation phenomenon. A community sample of 161 adolescents completed the Beck Depression Inventory-II (A. T. Beck, 1996) at Time 1, and then 88 returned 1 year later for an assessment of life events using a rigorous contextual interview and rating system. Consistent with hypotheses, and controlling for baseline stress, cognitive-affective symptoms of depression prospectively predicted higher levels of dependent interpersonal life events. In contrast, somatic symptoms prospectively predicted higher levels of independent life events. Further examination of the types of events generated by specific symptoms suggests that different mechanisms may drive specific patterns of symptom-event generation and suggests that broadening the definition of independence may be necessary to capture the full context of event generation.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.302
Teacher spread0.276 · 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 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

Citations51
Published2009
Admission routes1
Has abstractyes

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