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Record W4321387616 · doi:10.52214/gsjp.v7i.10791

The Development of Cognitive Vulnerability to Hopelessness Depression

2005· article· en· W4321387616 on OpenAlexafffund
Sabina Sarin, John R. Z. Abela

Bibliographic record

VenueGraduate Student Journal of Psychology · 2005
Typearticle
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsVulnerability (computing)Depression (economics)PsychologyCognitive vulnerabilityCognitionCognitive psychologyNeuroscienceDepressive symptomsComputer securityComputer science

Abstract

fetched live from OpenAlex

While several studies have supported the hopelessness theory’s claim that depressogenic inferential styles serve as vulnerability factors to depression, little research has examined how these styles develop. The current study examined three theories of their development in children between the ages of 7 and 13. Results supported two of these theories, indicating that children with pessimistic inferential styles report experiencing higher levels of specific negative life events than children without these styles. Furthermore, parents of children with a depressogenic inferential style about consequences provided more pessimistic feedback about the consequences of negative events in their child’s life than parents of children without this style. Results suggest that different pathways lead to the development of the three pessimistic inferential styles.

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)0.003
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.059
GPT teacher head0.424
Teacher spread0.366 · 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

Citations1
Published2005
Admission routes2
Has abstractyes

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