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Record W2153876640 · doi:10.1332/204080511x583823

The emergence of structured subnational voluntary sector–government relationships in Canada: a historical institutional analysis

2011· article· en· W2153876640 on OpenAlexaffabout
Peter R. Elson

Bibliographic record

VenueVoluntary Sector Review · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsMount Royal University
Fundersnot available
KeywordsVoluntary sectorGovernment (linguistics)TurnoverVoluntary associationPolitical sciencePublic administrationPublic economicsEconomicsManagement

Abstract

fetched live from OpenAlex

Building on prior research at the federal level, this paper examines the emergent institutional relationships between government and the voluntary sector in seven Canadian provinces. Prior to the release of a national survey in 2005, little collective attention was paid to the size and impact of the voluntary sector at the provincial level by either the sector or governments. This subnational historical institutional analysis reveals that there is a new and growing appetite for policy dialogue, representing a notable shift in attention to voluntary sector–government relations at the provincial level. Trends and informative exceptions in this emerging relationship are profiled.

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)0.013
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 score0.788
Threshold uncertainty score0.914

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.012
Science and technology studies0.0150.008
Scholarly communication0.0080.002
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.069
GPT teacher head0.258
Teacher spread0.189 · 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

Citations13
Published2011
Admission routes2
Has abstractyes

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