MétaCan
Menu
Back to cohort
Record W1995363444 · doi:10.5539/ass.v11n2p96

A Study on Sub-Clinical Narcissistic Personality Score and Its Relationship with Academic Performance-An Indian Experience

2014· article· en· W1995363444 on OpenAlexvenueno aff
Vaidhyanatha Balaji Kurumbur Varadharajan, Indradevi Balasundaram

Bibliographic record

VenueAsian Social Science · 2014
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsnot available
Fundersnot available
KeywordsNarcissismPsychologyPersonalityBig Five personality traitsClinical psychologyNarcissistic personality disorderPersonality Assessment InventorySocial psychologyPersonality disorders

Abstract

fetched live from OpenAlex

Sub-clinical narcissism is the presence of narcissistic personality traits in otherwise normal people. People with high levels of these traits said to have inflated self-esteem and possibly a high egotism. A 40 itemed Narcissistic Personality Inventory is used to measure this type of personality traits. Those individuals who score above 20 points from the available 40 points of NPI-40 Inventory is considered to be having higher levels of Subclinical Narcissism and prone to exhibit socially dislikeable personality traits. This study tried to address the relationship between supposedly negative personality traits of Sub-clinical Narcissism using NPI-40 Score against past and present academic performance of a group of students in a Private University setup. The study included 202 participants from a Business School Division of a Private University. Analysis showed that only at the current academic levels of the respondents, NPI-40 scores were significantly correlating with their academic performance. Research implications are discussed.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.175
GPT teacher head0.453
Teacher spread0.278 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueAsian Social ScienceSame topicPersonality Traits and PsychologyFrench-language works237,207