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Record W2741959638 · doi:10.1002/pmh.1384

Looking ahead through a fragile lens: Vulnerable narcissism and the future self

2017· article· en· W2741959638 on OpenAlexaff
David Kealy, Sharan Sandhu, John S. Ogrodniczuk

Bibliographic record

VenuePersonality and Mental Health · 2017
Typearticle
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsFraser HealthUniversity of British Columbia
Fundersnot available
KeywordsNarcissismOptimismPsychologyDistressMental healthClinical psychologyPersonal developmentSocial psychologyPsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

Empirical data are lacking with regard to the degree to which self-absorbed hypersensitivity may be related to perceptions of the future self. The purpose of this study was to examine the relationship between vulnerable narcissism and several components of future orientation among psychiatric outpatients. A sample of 132 adult outpatients seeking mental health services completed measures assessing vulnerable narcissism, optimism, personal growth initiative and symptom distress, along with several questions regarding specific future outcomes. Correlation and regression analyses were used to examine relationships between vulnerable narcissism and future outlook domains, controlling for sociodemographic confounds and symptom distress. Significant negative associations were found between vulnerable narcissism and optimism, personal growth initiative, and expectations regarding mental health recovery and personal goal achievement. Clinical implications of these findings are discussed. Copyright © 2017 John Wiley & Sons, Ltd.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.345
Teacher spread0.320 · 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

Citations16
Published2017
Admission routes1
Has abstractyes

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