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Record W4250121462 · doi:10.32920/ryerson.14639775

Women's voluntary organizations are different: their response to shifts in Canadian policy

2021· preprint· en· W4250121462 on OpenAlexaboutno aff
Agnes Meinhard, Mary K. Foster

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsnot available
Fundersnot available
KeywordsTurnoverVoluntary associationVoluntary sectorNeglectPoliticsPolitical scienceParagraphLiberalismPublic relationsManagementMedicineLawEconomicsNursing

Abstract

fetched live from OpenAlex

[Paragraph 1 of Introduction]: Although women make up more then half of Canada’s volunteers, and a large number of voluntary organizations are exclusively female, there has been little research focussing on women’s voluntary organizations. The purpose of this study is to correct this neglect by surveying 351 women’s voluntary organizations (as defined in the Methods section), and comparing them to 294 voluntary organizations that do not fall into the category of women’s organizations. Specifically, we investigate the responses of these voluntary organizations to the changes wrought by the neo-conservative political philosophy that has replaced the social democratic liberalism of the post-war era (see McBride and Shields, 1997). Keywords: CVSS, Centre for Voluntary Sector Studies, Working Paper Series,TRSM, Ted Rogers School of Management Citation:

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)0.005
metaresearch head score (Gemma)0.017
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 score0.953
Threshold uncertainty score0.340

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0110.003
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.018
GPT teacher head0.288
Teacher spread0.269 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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