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Record W4403034790 · doi:10.4324/9781003528432-4

Seniors' poverty in British Columbia, Canada

2024· book-chapter· en· W4403034790 on OpenAlexaboutno aff
Karen Lok Yi Wong

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPovertyGeographyHistoryPolitical scienceLaw

Abstract

fetched live from OpenAlex

This chapter discusses the issue of older adults’ poverty in British Columbia, Canada. Many older adults have an income from a pension that just meets or is slightly above the poverty line. However, they have high spending on basic needs. Low income but high spending cause many older adults to be in poverty. This chapter argues why older adult poverty is a social justice issue by referring to two social justice theories, the capabilities approach and the ethics of care perspective. By referring to the capabilities approach, the chapter suggests that the basic needs of many older adults are not met due to low income but high spending. This constrains older adults’ building of capabilities and their freedom of choice to achieve good lives. Regarding the ethics of care perspective, this chapter focuses on the relationship between older adults and society. It argues that society&s;s view of older adults as a burden accelerates older adults’ poverty. This chapter concludes that these theories should complement instead of compete with each other to explain why older adults’ poverty is a social justice issue.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.076
Threshold uncertainty score0.554

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0200.002
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.008
GPT teacher head0.217
Teacher spread0.209 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2024
Admission routes1
Has abstractyes

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