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Record W7036056507

Aging Black and Lonely: A Narrative Experience of Black Older Adults in Canada

2022· dissertation· en· W7036056507 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2022
Typedissertation
Languageen
FieldArts and Humanities
TopicLibraries and Information Services
Canadian institutionsnot available
Fundersnot available
KeywordsLonelinessSocial isolationNarrativePopulationPossession (linguistics)InterviewQualitative research
DOInot available

Abstract

fetched live from OpenAlex

Loneliness affects Black older adults (BOAs) in different and debilitating ways. BOAs aged 65 years and above make up 7.3% of the Black population and 15.9% of the total population of those aged 65 years and above in Canada. Also, the population of BOAs in Canada has doubled within the last two decades, highlighting the need to understand the unique experience of aging of this population, including their experiences of loneliness and social participation. Contrarily, there exist notable gaps within the loneliness literature on the experience of loneliness and social participation among BOAs living in Canada. This doctoral dissertation addresses these knowledge gaps by providing insight into the factors influencing social and emotional loneliness and lack of social participation among BOAs and proffers ways to address the issues, expressly informing future research, services, and programs targeting this group. This dissertation is comprised of four papers. Paper 1 is a scoping review of 27 articles that reveal the dearth of empirical evidence on the experience of loneliness or subjective social isolation and the contributing factors among BOAs in Canada. The data used for the remaining three papers were collected through 25 narrative interviewing conducted with 13 BOAs living in Hamilton and Windsor, Ontario. Findings from this paper shows that in addition to unavailability of social provisions (relational gains), loneliness among BOAs is exacerbated by socio-economic factors, health-related factors and behaviours, and technology, media device possession and usage. The results also indicate that there is need for inclusion of BOAs in loneliness research in Canada. Following Paper 1, Paper 2 investigates the unique experience of loneliness among BOAs living in Canada and the suitability of the social provision framework in identifying and understanding the experience of loneliness among this group. Findings from this paper demonstrates the significance of social connection, reliable relationships and relational gains in reducing and increasing experience of loneliness among BOAs. Paper 3 analyzes the constellation of factors that contribute to loneliness among BOAs and how they cope with their experience of loneliness. The results from this paper highlight the complex overlapping factors that contribute to the experience of loneliness among BOAs including time, sense of place and belonging, weak socio-personal interaction, and level of exclusions. Paper 4 and final paper uncovers the micro and macro level factors that hinder BOAs from participating in social programs and services and suggests ways to improve their social participation. Specifically, findings from this paper uncovers the need for programs and services that are culturally diverse and sensitive to the unmet needs of racialized and minoritized groups. Collectively, the four papers contribute to knowledge on the experience of loneliness among BOAs and contributory factors and highlight the need for more inclusive research and practice on addressing loneliness among this group.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.820

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.2220.000

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 head0.010
GPT teacher head0.180
Teacher spread0.170 · 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
Published2022
Admission routes1
Has abstractyes

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