“The Meaning of Me®”: A Canadian blueprint for addressing the complex whole that is the person at the centre of the community-based homecare services model
Bibliographic record
Abstract
The increasing focus on person-centeredness within current healthcare models is increasingly relevant to the growing demographic of socially vulnerable older adults living with complex care needs. According to the UK’s Social Care Institute for Excellence (SCIE), social isolation is “an imposed isolation from normal social networks caused by loss of mobility or deteriorating health”. Those in receipt of homecare in the community cite the importance of having home care meet their social and emotional needs, yet the consensus and the literature strongly supports the notion that public healthcare is barely able to provide basic personal supports let alone the increasingly important domain that encompasses, inter alia, the social and emotional needs of the older adult. In truth, whether one is addressing the physical or the psychosocial, the conceptual model of personhood remains the same. It is the actionable elements of the model that differ. Since the dimensions of the non-clinical psychosocial frame extend, inter alia, to the social, emotional, creative, existential, cultural, active and physical and community engaged, we believe that engagement with this domain, for the socially vulnerable older adult, warrants a far deeper architecture than both current funding and the narrow task focus of community care is able to provide. This paper defines person-centered care at the furthest point along the chain of care. This is the point occupied by homecare supports in the community. It references a working model of person-centeredness focused on the rich domain of the non-clinical psychosocial. Its two primary dimensions of focus are those of the mind and the “place”, or an ecological/community integrated model of higher order needs. It has three distinct levels of interaction: one designed to create an alternate lens of communication that lies outside of the domain of physical and mental impairment that helps build knowledge of and communication with personhood; an organised process for developing interests and activities with a focus on creative space, new experience, control, autonomy and intrinsic capacity and, finally, a working blueprint for wider community interaction and integration.
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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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.021 | 0.064 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.010 | 0.029 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".