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Record W2610976295

“Irrational” Organizations: Why Community-Based Organizations Are Really Social Movements

2000· article· en· W2610976295 on OpenAlexaboutno aff
Mark J. Stern, Susan C Seifert

Bibliographic record

VenueScholarlyCommons (University of Pennsylvania) · 2000
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIrrational numberSocial organizationSocial movementPublic relationsPolitical scienceBusinessSociologySocial scienceLawPolitics
DOInot available

Abstract

fetched live from OpenAlex

This paper was prepared for the Planners Network Conference 2000 in Toronto. The focus of the paper is a re-conceptualization of community-based organizations from a model of a classic nonprofit institution to that of a social movement. Our observations are based on intensive evaluation of about 40 community-based arts organizations in Philadelphia involved in the Culture Builds Community initiative (1997-2001) of the William Penn Foundation. We argue that these small organizations have been colonized by business school consultants who want them to act and look like more established nonprofits. In our view, these organizations are better conceptualized as 'social movements' rather than—potentially—rational organizations. Changing the conceptual framework in this manner changes the definition of terms like 'capacity-building' and 'sustainability.' In addition, it shifts the 'unit of analysis' from individual organizations to the social networks in which they operate.

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)0.012
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0100.069
Scholarly communication0.0140.013
Open science0.0020.006
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.201
Teacher spread0.183 · 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 designTheoretical or conceptual
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

Citations5
Published2000
Admission routes1
Has abstractyes

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