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Record W4399772101 · doi:10.36315/2024inpact071

Co-living as a choice for independent retired women: Hope for social transformation

2024· book-chapter· en· W4399772101 on OpenAlexfundaboutno aff

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyTransformation (genetics)GerontologyMedicineBiology

Abstract

fetched live from OpenAlex

In this paper we present the results of a study of a successful co-living project for independent retired women.As our societies are increasingly concerned with sustainable living, we see that aging populations are often overlooked.Yet there is going to be an increase on these populations.During COVID in the Canadian context, some grave concerns were raised around retirement homes.For instance, by not allowing visitors the aging, already feeling lonely, were further cut-off from needed family social contact.Living close together in their common space increased major health issues with higher percentages of death.There were also increasing numbers of fires with significant numbers of deaths.Moreover, retirement homes are costly.With increasing financial constraints in many countries, older people feel financial burdens and there is a need to reconsider the conditions in which older people are finding themselves.Spontaneous groupings and living together experiments have generally failed.Even friends living in a house together usually experience issues after a few years.We investigated the successful Babayaga House co-living model in Paris that has been successful for over 12 years to uncover characteristics that are favorable for such projects to continue to strive.Through the analysis of journals and other documents found in the public domain we uncovered desirable attitudes and qualities to help identify social factors that can lead to such a sustainable governance model.The method used was qualitative.To understand the complexity of the underpinnings of the system we recruited volunteers to make regular journal entries over six months.We also carried out a literature search to identify recognized questionnaire models that could be useful to map out the criteria for our study.The journal entries and additional documentation from the public domain were analyzed for emergent themes.Then these were paired with relevant entries from the existing well-being questionnaires identified in the literature search.We discuss our findings and present an articulation of the main concepts behind the successful functioning of the French model, also taking into account some of the major issues identified.Among major themes uncovered were autonomy, collaboration, accountability, the need for a number of positive traits like positive emotions, positive relationships and positive thinking with a total of 33 themes.

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)0.008
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.023
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0230.014
Scholarly communication0.0110.007
Open science0.0020.013
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0090.001

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 head0.189
GPT teacher head0.427
Teacher spread0.238 · 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 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
Published2024
Admission routes2
Has abstractyes

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