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Record W19140480 · doi:10.24972/ijts.2009.28.1.68

A Viable Model and Self-Report Measure of Spiritual Intelligence

2009· article· en· W19140480 on OpenAlexafffund
David B. King, Teresa L. DeCicco

Bibliographic record

VenueInternational Journal of Transpersonal Studies · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsTrent University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologySpiritual intelligenceReligiosityMeaning (existential)Scale (ratio)Reliability (semiconductor)Measure (data warehouse)Social psychologyConstruct validityConstruct (python library)Transcendental numberPsychometricsClinical psychologyEmotional intelligencePsychotherapistEpistemologyComputer scienceData mining

Abstract

fetched live from OpenAlex

A four-factor model of spiritual intelligence is first proposed. Supportive evidence is reviewed for the capacities of critical existential thinking, personal meaning production, transcendental awareness, and conscious state expansion. Based on this model, a 24-item self-report measure was developed and modified across two consecutive studies (N = 619 and N = 304, respectively). The final version of the scale, the Spiritual Intelligence Self-Report Inventory (SISRI-24), displayed excellent internal reliability and good fit to the proposed model. Correlational analyses with additional measures of meaning, metapersonal self-construal, mysticism, religiosity, and social desirability offer support for construct and criterion-related validity. According to both intelligence criteria and current psychometric standards, findings validate the proposed model and measure of spiritual intelligence. Future directions 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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.072
GPT teacher head0.398
Teacher spread0.326 · 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

Citations257
Published2009
Admission routes2
Has abstractyes

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