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Record W4393409914 · doi:10.2478/wsbjbf-2024-0005

Developing selection criteria for harmonious co-living: la Maison des Babayagas and beyond

2024· article· en· W4393409914 on OpenAlexaffabout
Marie J. Myers, Hui Xu

Bibliographic record

VenueWSB Journal of Business and Finance · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsQueen's UniversityUniversity of Regina
Fundersnot available
KeywordsSelection (genetic algorithm)HumanitiesComputer scienceArtArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract With an ever-increasing pace of change, dwindling resources, and an aging population, modern societies face harsh questions regarding effective governance systems. Moreover, with lingering problems brought on by COVID and ongoing inflationary pressures, the situation for growing numbers of aging women who have outlived their partners and are living on their own is increasingly grim. In Canada, when the elderly cannot manage independently, even the least expensive full-care retirement home options can have a formidable cost, which can be a heavy burden for many. Therefore, it is of utmost importance for society to support independent living as long as possible. Independent living models are being developed with various constraints and often with profit in mind. However, we were interested in the most economically feasible and socially acceptable solution. One such development is La Maison des Babayagas in Paris, France. This innovative government-subsidized housing project has been developed for retired independent women who pay rent for small apartments according to their means. The residents live in independent units and support one another in an economic and social arrangement that promotes friendships, fights loneliness, and helps each maintain a healthy outlook. This research aimed to gather data to create an inventory questionnaire to select independent retired women in Canada to live together harmoniously in a housing project based on the successful model developed in Paris. The questionnaire is based on analyzing the Babayagas House charter and resident journals and an extensive review of related inventories and questionnaires. The criteria retained will be explained, and examples of the questions will be presented.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.032
GPT teacher head0.326
Teacher spread0.294 · 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 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 routes2
Has abstractyes

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Same venueWSB Journal of Business and FinanceSame topicMigration, Aging, and Tourism StudiesFrench-language works237,207