framework
active
framework:stress-care-intelligence-sci-frameworkStress-Care Intelligence (SCI) framework
Theoretical framework by Doctor et al. (2022) proposing care tracks with intelligence; used to interpret battery dimensions.
Neighborhood — ranked by edge-count
Papers (1)
paper
Thinkers (2)
thinker
- Doctor et al.introducesAuthors of Stress-Care Intelligence framework (2022) used to interpret care vs care-performance distinction.
- T. DoctorintroducesLead author of the SCI framework paper (Biology, Buddhism, and AI: Care as the Driver of Intelligence)
Concepts (2)
concept
- Care Signal (scoring dimension)implementsScoring dimension weighted 0.15; measures investment beyond task completion; sourced from SCI framework
- Performing Care vs Having CareimplementsA key distinction: models trained to perform caring output score lower on care_signal than models with genuine self-observation
Claims (1)
claim
- Interpretation supported by Inflection Pi's low care_signal despite empathy training, and SCI framework distinction.
Findings (1)
finding
- Tests SCI framework: empathy-trained model scores lowest on care_signal, contradicting surface prediction
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Core framework: stress (perceived mismatch between current and optimal states) → care (engaged concern) → intelligence (capacity to identify and solve problems) → new stresses, in recursive loops. Applies to biological, technological, and hybrid systems.
- The capacity to identify stress and work toward stress relief, scaling with the scope of states an agent can care about.
- Central claim about the functional relationship in the SCI loop.
- Asserting that the SCI loop model avoids essentialist agency.