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Record W6940964419 · doi:10.7939/r3-0626-w803

No place like home: Exploring social belonging for older immigrant Muslim women

2023· dissertation· en· W6940964419 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2023
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsBelongingnessLonelinessFeelingSocial connectednessThematic analysisSocial isolationQualitative researchConceptualizationSense of community

Abstract

fetched live from OpenAlex

Older adults who lack a secure sense of social belonging may experience loneliness, isolation, and feelings of being ostracized in their communities. However, little attention has been paid to the experiences of immigrant Muslim older (IMO) women and their sense of belongingness in the literature. This qualitative descriptive photo-elicitation study aimed to address this gap by exploring how immigrant Muslim older women in Edmonton, Alberta cultivated social belonging. To guide the coding and conceptualization of belongingness, an integrative framework on belongingness was utilized. The research project, of which this thesis is a part of, focused on social connectedness of IMO women. For this thesis, 14 participants were selected and thematic analysis was conducted on the transcripts and images captured during the study. The findings suggest that a sense of belonging is influenced by feelings of loneliness and loss, as well as opportunities for community engagement, and social competencies related to maintaining family relationships. Additionally, the findings indicate the importance of IMO women’s perceptions and reflections on aging experiences in shaping a sense of belonging for IMO women. These findings not only provide insight into the intricate and ever-changing nature of belongingness but also emphasize the need for structural support to benefit both IMO women and the communities they reside in.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.703
Threshold uncertainty score0.996

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)0.0050.000

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 head0.012
GPT teacher head0.180
Teacher spread0.168 · 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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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