Ontological exercises to overcome mismatch diseases’ obstacles to holistic health
Bibliographic record
Abstract
The current urban environment inhabited by humans in North America reflects profound changes in its physical and social architecture that occurred more rapidly than the human biological capacity to adapt. This mismatch between self and environment can result in ailments and diseases that are physical (e.g. metabolic syndrome) and psychological (e.g. anxiety, depression). These mismatch ailments act insidiously, as their chronic/diffuse nature makes them go generally unnoticed. However, their effects are no less important on overall wellbeing and deserve attention from health professionals. The overarching hypothesis is that ontological exercises, i.e. practices that are aimed to foster a deeper understanding of the nature of being, promote holistic health to counterbalance the feeling of threat arising from the disconnect between post-modern society and the ancestral makeup of human beings. Numerous cultural practices have emphasized exercises aimed at operating transformative changes to increase wellbeing, empathy, compassion and pro-social behaviors. Ontological exercises from ancient Greeks, Buddhists and Native Americans will be explored in this context.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".