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Record W2061630689 · doi:10.1332/204080510x497019

Strengthening government–nonprofit relations: international experiences with compacts

2010· article· en· W2061630689 on OpenAlexaboutno aff
John Casey, Bronwen Dalton, Rose Melville, Jenny Onyx

Bibliographic record

VenueVoluntary Sector Review · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsnot available
Fundersnot available
KeywordsPolityParallelsGovernment (linguistics)NarrativePublic administrationPolitical scienceNonprofit sectorPublic relationsPoliticsEconomicsLaw

Abstract

fetched live from OpenAlex

Governments around the world have sought to strengthen their relations with nonprofit organisations. In many jurisdictions this has led to the development of written framework agreements between government and the nonprofit sector, most commonly known as compacts . They have had widely differing impacts – some are seen as successful initiatives that have significantly strengthened relations between government and nonprofits, while others have had little effect and have been quickly discarded or ignored. This paper documents the recent evolution of such processes in the UK, Canada, Australia, the US, France, Estonia and Spain, and explores the parallels between them. The narratives from these countries illustrate an emerging common discourse, but also that the peculiarties of each polity have led to significantly different substantive outcomes.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.945
Threshold uncertainty score0.992

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.017
GPT teacher head0.293
Teacher spread0.276 · 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.

Study designNot applicable
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

Citations29
Published2010
Admission routes1
Has abstractyes

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