Symbiotic care between residents in service-integrated housing
Bibliographic record
Abstract
Purpose Sustainable solutions for meeting the physical, emotional and social health care needs of individuals may be realized by shifting the care landscape; for instance, through innovative models of service-integrated housing (SIH). By diversifying populations in these settings, care recipients can choose to engage their skills and abilities toward assisting co-residents, and vice versa as a form of symbiosis. The purpose of this paper is to define attributes of the concept and practice of symbiotic care. Design/methodology/approach The authors drew on firsthand field experience and secondary data from a literature review to conduct a conceptual derivation and analysis, using Walker and Avant’s methodology. The term symbiotic mutualism was derived from the field of biology as an analogy for care exchanged between non-peer co-residents. Attributes, antecedents and consequences of symbiotic care were identified and illustrated using model, borderline and contrary case descriptions. Findings Four defining attributes of symbiotic care were identified: first, cohabitation: care recipients live closely together in SIH settings. Second, non-peer: co-residents have distinct, complementary needs and abilities. Third, mutualism: co-residents experience mutually significant benefits as a result of the activities of their co-residents. Fourth, agency-sponsored: the professional SIH agency or organization attends to unmet resident needs. Research limitations/implications Symbiotic care is a relatively rare phenomenon for which little research exists. This analysis provides a starting point for empirical research, policy and program development and critical evaluation. Originality/value This paper fills a wide gap in the research literature and offers important terminology. It is the first to define the attributes of symbiotic care.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".