Applications of the Metatheory of Resilience and Resiliency in Rehabilitationand Medicine
Bibliographic record
Abstract
This presentation will based upon the “Metatheory of Resilience and Resiliency” which was described in the 2002 issue of the Journal of Clinical Psychology. The techniques that are applicable to health care providers are adaptations from the Personal Resiliency Training Guidebooks. Description The theoretical model of resiliency will be explained as a process—a personal journey through disruption and reintegration. The model will demonstrate the incremental process and series of choices evident in progression toward optimal health. The key stage in the re-occurring model is the trough of disruption. It is in chaos and the discomfort of leaving homeostasis that helping professionals can facilitate the experience of digging through superficial protective layers of consciousness to discover innate resilience. Resilience is a progressive force within everyone that drives them to maximize, embrace, and fulfill potentials. In most individuals, resilience is the drive to be in harmony with a source of energy beyond themselves. Techniques to facilitate the discovery of essential, character, noble, synergistic, ecological, universal, and orchestrational resilience for health practitioners will be described.
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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 | 0.086 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.019 | 0.011 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.008 | 0.013 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".