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Record W7028698104

Exploratory Research: An Intergenerational Program in a CHSLD/RPA

2022· dissertation· en· W7028698104 on OpenAlexaboutno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2022
Typedissertation
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutionNegotiationElaborationExploratory researchQualitative researchQuality of life (healthcare)
DOInot available

Abstract

fetched live from OpenAlex

The present study sought to explore the impact of an intergenerational program occurring in a Quebecois CHSLD/RPA on the residents' end-of-life course. It focuses on later life experiences and the particularities of living and aging in an institution offering this kind of initiative while taking into consideration the current context. An immersion into their "milieu de vie" allowed to conceptualize four main experiences: \n•\tTheir Admission and Transition Process \n•\tTheir Integration and Daily Living \n•\tThe Elaboration and Participation in an Intergenerational Program \n•\tThe Pandemic \nSemi-structured qualitative interviews were conducted with three coordinators and three residents. \nWhat it is to live and age in this kind of institution is not linear; it is a negotiation with oneself and others and an ongoing process. There is no clear definition of aging properly either, but at the root of their testimonies, we can find that key elements can improve or impede the quality of end-of-life.

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)0.004
metaresearch head score (Gemma)0.003
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 score0.315
Threshold uncertainty score0.626

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.007
Scholarly communication0.0030.001
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.084
GPT teacher head0.371
Teacher spread0.286 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

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