Unpredictable Paths into Care: Examining HIV and MS Care Relationships in Southern Ontario
Bibliographic record
Abstract
In Canada, we often speak of caring for others as more than a social obligation; it is part of how we conceptualize ourselves and our humanity. Family/friend relationships can become strained, however, when providing care and support for people with complex and unpredictable chronic episodic illnesses, here termed episodic care. Relational impacts may be understood as influences and impacts directly related to the relationship between the carer and family member/friend. The purpose of this study is to create a middle-range grounded theory of episodic caring based on the relational impacts of carers for people living with HIV and MS.\nConducted in southern Ontario using qualitative constructivist grounded theory methods, this dissertation examines the development of relationships between carers and family members/friends living with episodic illnesses and documents the resulting social, emotional, and relational impacts on carers. To better understand how family/friend episodic care relationships emerge and progress, this dissertation project was guided by the emergent research question: What are the relational impacts of episodic care on HIV and MS carers?’ Findings from semi-structured interviews with 18 HIV and MS carers highlight the development of a relational identity as carers navigate shifting illness episodes over time. The relational model of episodic care developed in this study presents an alternative conceptualization of carer identity development by integrating episodes of illness and wellness into chronic illness care. The model illustrates the intimate, evolving relationship between the carer and family member/friend living with an episodic illness.\nThe study findings describe a phased approach to relational identity development involving entries into care, navigating unpredictability, and redefining the care relationship. This develops into an identity of essential carer or reciprocal carer, or carers may choose to exit care. Resolving relational tensions that arise from performing care activities creates an opening for changes in how carers understand themselves through their care relationships. In addition to how episodic carer identities influence how carers perceive themselves within a relationship, social factors such as gender, income, and culture impact care experiences, at times creating additional challenges in the lives of episodic carers. To reduce carer strain, a re-visioning of family/friend care as community-centred and family/friend-supported will help re-focus episodic care as an option instead of a duty.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".