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Record W4403602179 · doi:10.61959/disx1332e

A Snapshot of Grandparents in Canada (May 2019 Update)

2019· report· en· W4403602179 on OpenAlexaboutno aff
Nathan Battams

Bibliographic record

Venuenot available
Typereport
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsnot available
Fundersnot available
KeywordsSnapshot (computer storage)GrandparentGeographyGenealogyComputer scienceHistoryPsychologyDatabaseDevelopmental psychology

Abstract

fetched live from OpenAlex

Canada’s grandparents are a diverse group. Many of them contribute greatly to family functioning and well-being in their roles as mentors, nurturers, caregivers, child care providers, historians, spiritual guides and “holders of the family narrative.”As Canada’s population ages and life expectancy continues to rise, their presence in the lives of many families may also increase accordingly in the years to come. With the number of older Canadians in the workforce steadily increasing, they are playing a greater role in the paid labour market – a shift felt by families who rely on grandparents to help provide care to their grandchildren or other family members. All the while, the living arrangements of grandparents continue to evolve, with a growing number living with younger generations and contributing to family households.Using newly released data from the 2017 General Social Survey, we’ve updated our popular resource A Snapshot of Grandparents in Canada, which provides a statistical portrait of grandparents, their family relationships and some of the social and economic trends at the heart of this evolution.

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)0.001
metaresearch head score (Gemma)0.004
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: Other · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.206

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0070.015
Science and technology studies0.0040.000
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0410.008

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 head0.020
GPT teacher head0.301
Teacher spread0.281 · 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
GenreOther

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

Citations1
Published2019
Admission routes1
Has abstractyes

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