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Record W2061075867 · doi:10.1348/000712608x396585

Validation of the Narrative Emplotment Scale and its correlations with well‐being and psychological adjustment

2009· article· en· W2061075867 on OpenAlexaff
Eric Hill, Heather K. Terrell, Steven Hladkyj, Craig T. Nagoshi

Bibliographic record

VenueBritish Journal of Psychology · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPsychologyReligiosityLocus of controlPersonalityIncremental validitySocial psychologyPsychometricsNarrativeConstruct validityClinical psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Two studies examined correlates of the Narrative Emplotment Scale (NES), which measures the extent to which individuals perceive chance events and unchosen experiences as meaningfully connected. In Study 1 (N=99), the NES demonstrated adequate test-retest stability and good internal reliability. The scale was positively related to paranormal beliefs, mystical experiences, and absorption. In Study 2 (N=342), personality measures indicative of external locus of control, intrinsic religiosity, well-being, satisfaction with life, and a measure of frequency of coincidence experience were all positively correlated with narrative emplotment, providing further support for the construct validity of the scale. In terms of the question of whether meaning making is predictive of better or worse psychological adjustment, analyses indicated that the relationship between narrative emplotment and psychological adjustment was moderated by individual differences in coping strategies. Path analysis indicated that emplotment was a mediator of the pathway between religiosity and well-being. Emplotment had a negative effect on well-being through chance locus of control. These analyses suggest that this type of meaning-making is an important variable for understanding religious/spiritual beliefs and their influence on psychological adjustment.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.658
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

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

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 head0.038
GPT teacher head0.369
Teacher spread0.331 · 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 teacher head, 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

Citations4
Published2009
Admission routes1
Has abstractyes

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