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Record W4399025036 · doi:10.1016/j.jaging.2024.101236

Aging with her garden: Mutual care across species and generations

2024· article· en· W4399025036 on OpenAlexaffabout
Constance Dupuis

Bibliographic record

VenueJournal of Aging Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsMcMaster University
FundersH2020 Marie Skłodowska-Curie ActionsHorizon 2020European Commission
KeywordsSociologyAutoethnographyNarrativeNormativeGender studiesEmbodied cognitionPhotovoiceAestheticsEpistemology

Abstract

fetched live from OpenAlex

What can caring for, and being cared for by, a garden teach us about aging well? This article is a narrative exploration of care, aging, and wellbeing in later life through conversations with an older woman and her garden in Toronto, Canada during the months of the COVID-19 pandemic. The focus is on the interconnectedness of care across generations and species. Moving away from conventional generational scripts, the article expands notions of care and aging with an intersectional, feminist and decolonial approach to relationality across time and space. The article uses interviews, photovoice-inspired sessions, and autoethnography, to look at aging and wellbeing as relational and more-than-human relationality. It extends the ethics of care beyond traditional boundaries, embracing perspectives that challenge normative assumptions of gender, age, and interspecies relations. The article aims to contribute to the current debates around colonial research logics, though a critical feminist understanding of relationality and embodied learning. It emphasizes the importance of connecting across generations, seeing land as a way to restore human and more-than-human relations while prefiguring a more care-full present.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.878

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.046
GPT teacher head0.393
Teacher spread0.347 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2024
Admission routes2
Has abstractyes

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