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Record W2945401103 · doi:10.22230/cjnser.2019v10n1a282

Nonprofit adaptation and variation in changing contexts: The speciation of shared platform organizations

2019· article· fr· W2945401103 on OpenAlexaffvenueabout
R. de O. Dart, Olakunle Akingbola, Katie Allen

Bibliographic record

VenueCanadian journal of nonprofit and social economy research · 2019
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicService and Product Innovation
Canadian institutionsLakehead UniversityUniversity of GuelphTrent University
Fundersnot available
KeywordsSociologyBricolageAdaptation (eye)HumanitiesManagementPolitical sciencePsychologyArt

Abstract

fetched live from OpenAlex

This research examines the structure, organization, and evolution of the shared platform, an innovative organizational structure intended to assist the capacity concerns of small nonprofits. The grounded and exploratory inquiry of multiple participants in a shared platform organizational community in Toronto shows that there are two distinct variants of the shared platform, and that the evolution of an administrative form to a community development form of shared platform occurred through a process of field-level bricolage.Cette recherche examine la composition, l’organisation et l’évolution de la plateforme partagée, une structure organisationnelle innovatrice conçue pour aider les petites associations sans but lucratif qui se soucient de leurs limites de capacité. Cette enquête ancrée et exploratoire de participants multiples dans une communauté organisationnelle à plateforme partagée à Toronto montre qu’il y a deux variantes distinctes de la plateforme partagée, et que son évolution d’une forme « administration » vers une forme « développement communautaire » s’est effectuée par un processus de bricolage sur le terrain.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.272
Teacher spread0.217 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2019
Admission routes3
Has abstractyes

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