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Record W3126988289

Caregiver Experiences with Publicly Funded and Privately Financed Home Care in Ontario

2020· dissertation· en· W3126988289 on OpenAlexaboutno aff
Alla Yakerson

Bibliographic record

VenueYork University Digital Library (York University) · 2020
Typedissertation
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
Fundersnot available
KeywordsRestructuringBusinessHealth carePublic sectorResidencePopulationPrivate sectorIndependence (probability theory)Economic growthPublic economicsMedicineEconomicsFinanceDemographic economicsEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

Home care is an integral aspect of Ontarios health care system. Services provided to individuals may allow them to live with independence within the comfort of their own residence. Over the last decade the demand for home care has risen substantially due to a number of factors including: the growing population, the rising share of individuals over the age of 65, the increasing rates of complex and chronic conditions, trends to faster hospital discharge, and advances in treatments/technologies. Simultaneously, the rise in neoliberalism has led to the restructuring of financing and delivery of health care through market-based models. While ostensibly an attempt to reduce public spending, it is more likely a result of an ideological shift away from state-provided care towards market-oriented service provision. In light of this, in the home care area, the state has been able to reduce its financial obligations by enabling privatization in the sector. The significance of policy change in the home care system and the decisions regarding the balance of the public/private scheme, therefore, have had serious implication for the experiences of those who provide the care the unpaid Informal Family Caregivers (IFC). 
\n\tAt present, public funding and provision of care have not kept up with the demand for services, thereby, encouraging individuals to turn to the private market if they find inadequacies in the delivery of publicly funded local home care services (McGregor, 2001). In light of this, the purpose of this study is to examine the lived experiences of IFC who seek services for their relatives from the public home care system as well as from the private marketplace. In doing so, the goal is to understand the circumstances and challenges faced by these caregivers in accessing care in each of these two systems and obtaining respite from their duties. This knowledge is fundamental to the health care system which seeks to prevent the institutionalization of individuals as well as to minimize health care costs associated with the physical and psychological outcomes of caregiving which may differ in quality.
\n\tThis study is influenced by the work of FP economists to explain inequities in health as stemming in part from the unequal division of labour in society by which women must both gain paid employment and carry out household work (cleaning, cooking, laundry, gardening, taking care of children and the elderly etc.). FPE further draws on the Social Determinants of Health (SDOH) concept, which considers how the organization, and distribution of resources such as income and health services interact with the social location of gender to impact health outcomes. 
\n\tThe qualitative research approach of descriptive phenomenology is employed to convey and understand the lived experiences of IFC with both the publicly funded and privately financed home care systems in and around the Greater Toronto Area. Quantitative analysis is further used to complement the voices of the participants. 
\n\tBy illuminating micro-level individual experiences in relation to broader political and economic context, the development of new theories can take place and lead to further investigations pertaining to the phenomenon of interest. By generating knowledge and creating awareness, the ultimate goal is to influence policies of care and service provision to address issues concerning equity and health.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.207
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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