The Noetic Signature Inventory: 12-Factor Confirmatory Factor Analysis
Bibliographic record
Abstract
Disclaimer: This manuscript is a preprint and has not yet been peer reviewed. The findings, interpretations, and conclusions presented here are subject to revision based on peer review. Readers are encouraged to view this version as a work in progress and to consult the final published version once available.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. Methods: In a cross-sectional study, 2,415 participants completed demographic information and the NSI. The collected data were then subjected to a confirmatory factor analysis (CFA). Results: Participants were 51.7 ± 15.0 years old with 16.7 ± 3.3 years of education. They hailed from 76 countries, although most were from the United States, the United Kingdom, and Canada. The CFA results for the 12-factor model were as follows: χ²(836) = 3962.74, p < .001, CFI = 0.981, TLI = 0.979, RMSEA = 0.039 (90% CI = 0.039–0.041), and SRMR = 0.048. All 44 items had factor loadings above the 0.50 cutoff, ranging from 0.86 to 1.83 (M = 1.12). These values represent a very good model fit to the data, as commonly reported fit statistics indicate. Conclusions: The 12-factor structure of the NSI was confirmed with excellent fit indices, supporting its potential as a valid and reliable tool for assessing noetic characteristics. Nonetheless, limitations remain, and further research is needed to confirm and extend the findings in diverse populations and settings. The results contribute to our understanding of the multidimensionality of noetic 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 methods to deepen understanding of inner knowing experiences.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".