Validation of the Awareness Atlas—a new measure of the manifestation of consciousness
Bibliographic record
Abstract
Consciousness has intrigued philosophers and scholars for millennia and has been the topic of considerable scientific investigation in recent decades. Despite its importance, there is no unifying definition of the term, nor are there widely accepted measures of consciousness. Indeed, it is likely that consciousness-by its very nature-eludes measurement. It is, however, possible to measure how consciousness manifests as a lived experience. Yet here, too, holistic measures are lacking. This investigation describes the development and validation of the Awareness Atlas, a measure of the manifestation of consciousness. The scale was informed by heart-based contemplative practices and the resulting lived experience with a focus on the impacts of manifestation of consciousness on daily life. Four hundred forty-nine individuals from the USA, Canada, India, and Europe participated in psychometric testing of the scale. Exploratory and confirmatory factor analyses were used for validation, demonstrating excellent validity in measuring manifestation of consciousness. The final model fit exceeded all required thresholds, indicating an excellent fitted model with a single dimensionality to measure the manifestation of consciousness comprised of four subscales: Relationship to Others; Listening to the Heart; Connection with Higher Self; and Acceptance and Letting Go. Number of years meditating and practicing Heartfulness meditation were positively related to the total and subscale scores. Test-retest reliability was excellent for the total scale, and good to excellent for the four subscales. Findings demonstrate that the Awareness Atlas is a well-constructed tool that will be useful in examining changes in manifestation of consciousness with various experiences (e.g., meditation, life-altering conditions).
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 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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".