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The Noetic Signature Inventory: 12-Factor Confirmatory Analysis

2023· preprint· en· W4384206852 on OpenAlexaboutno aff
Helané Wahbeh, Michael Kriegsman

Bibliographic record

VenueF1000Research · 2023
Typepreprint
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsnot available
Fundersnot available
KeywordsConfirmatory factor analysisStatisticPsychologyStructural equation modelingDemographyMedicineStatisticsClinical psychologyMathematicsSociology

Abstract

fetched live from OpenAlex

<ns4:p>Background The Noetic Signature Inventory (NSI) is a 44-item self-report questionnaire that evaluates people’s experiences of intuition or inner knowing. Previous research developing and validating the measure demonstrated its validity and reliability, and a 12-factor model describing the variability of noetic experiences was found. This current study aims to confirm this factor model in a new population. </ns4:p><ns4:p> Methods In a cross-sectional study, 1,752 participants completed demographic information and the NSI. Confirmatory Factor Analysis was conducted on the collected data. </ns4:p><ns4:p> Results Participants were 49.3 ± 14.8 years old with 16.6 ± 3.4 years of education. They hailed from 62 countries although most were from the United States, United Kingdom and Canada. The CFA results for the 12-factor model were as follows: the chi square statistic equaled 2866.65 with 836 degrees of freedom and p &lt; .001. The model diagnostics demonstrated a very good model fit to the data. All 44 items had factor loadings above the 0.5 cutoff, ranging from 0.58 to 0.77, with an average factor loading of 0.71. </ns4:p><ns4:p> Conclusions The 12-factor structure of the NSI was confirmed, supporting its potential as a valid and reliable tool for assessing noetic characteristics. However, there are limitations to consider, and further research is needed to confirm and extend the findings in diverse populations and settings. The findings contribute to our understanding of the multidimensionality of these phenomena. Future research could build upon these findings by replicating the factor structure of the NSI in other populations, incorporating objective measures, conducting longitudinal studies, exploring underlying mechanisms, and using qualitative research methods to gain a deeper understanding of inner knowing experiences.</ns4:p>

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0100.006

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 head0.144
GPT teacher head0.430
Teacher spread0.286 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2023
Admission routes1
Has abstractyes

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