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Record W2181268918

Leaders of change: Social entrepreneurship and the creation of ecologies of solutions

2009· article· en· W2181268918 on OpenAlexaff
Kathia Castro Laszlo

Bibliographic record

VenueALAR · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Socioeconomic Development
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsAction (physics)Bridge (graph theory)EntrepreneurshipPublic relationsSociologyProcess (computing)Social changeSocial entrepreneurshipSocial learningSustainable developmentPolitical sciencePedagogy
DOInot available

Abstract

fetched live from OpenAlex

The line of inquiry on evolutionary learning communities (ELCs) to promote evolutionary development (ED) seeks to identify the conditions by which people can self-organize to learn, design and implement actions that will improve their quality of life and their socio-ecological milieu. In the Fall of 2007, the Universal Forum of Cultures took place in the city of Monterrey, Mexico. This UNESCO sponsored world event offered an opportunity to implement an evolutionary learning community with local citizens to bridge the knowledge of the Forum with the sustainable development needs of the local community. Over two hundred citizens responded to the call to join the “Leaders of Change” initiative. The ELC was conceived as a group of potential social entrepreneurs who came together to learn, identify possibilities, and support each other in the development of projects to translate their vision into action. This article reports on the design, process, and outcomes of the 8 month action-research project as well as the outcomes, reflections from the experience and implications for future research.

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)0.000
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 score0.929
Threshold uncertainty score0.102

Codex and Gemma teacher scores by category

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

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 head0.087
GPT teacher head0.266
Teacher spread0.179 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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