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Record W2151307958 · doi:10.1177/0899764001302009

Comparing Member-Based Organizations within a Social Economy Framework

2001· article· en· W2151307958 on OpenAlexaff
Jack Quarter, Jorge Sousa, Betty Jane Richmond, Isla Carmichael

Bibliographic record

VenueNonprofit and Voluntary Sector Quarterly · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsInstitute for Christian Studies
Fundersnot available
KeywordsGovernment (linguistics)Multivariate analysis of varianceSocial economySocial organizationBusinessDemocracyPublic relationsEconomicsMarket economyPolitical scienceSociology

Abstract

fetched live from OpenAlex

The purpose of this study is to determine whether nonprofits that serve a membership (that is, mutual nonprofits) have more in common with cooperatives (also member-oriented associations) than with nonprofits that are oriented toward the public. A MANOVA was used to analyze the effect of organizational type of which there were four categories (publicly oriented nonprofits, mutual nonprofits, cooperatives without shares, and cooperatives with shares) on the five dependent measures (social objectives, volunteer participation, democratic decision making, government dependence, and market reliance) derived from the social economy framework. The results offer some support for the hypothesis that serving a membership is an important factor in the basic characteristics of an organization, and that is true regardless of whether the incorporation is nonprofit or cooperative. However, charitable status also appeared to influence on the results. The implications for the social economy and civil society are discussed.

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)0.006
metaresearch head score (Gemma)0.019
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.037
GPT teacher head0.293
Teacher spread0.256 · 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

Citations31
Published2001
Admission routes1
Has abstractyes

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