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Record W2592637757 · doi:10.22230/cjc.2017v42n1a3103

Social Innovation Partnerships: An Opportunity for Critical, Activist Scholarship

2017· article· en· W2592637757 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Communication · 2017
Typearticle
Languageen
FieldComputer Science
TopicOpen Source Software Innovations
Canadian institutionsBrock University
Fundersnot available
KeywordsScholarshipSocial innovationDigital scholarshipPublic relationsLiteracySociologySpace (punctuation)Political scienceCritical mass (sociodynamics)Media studiesLibrary scienceSocial sciencePedagogyComputer science

Abstract

fetched live from OpenAlex

From 2013–2015, I was a Mitacs Elevate postdoctoral fellow with Mozilla. The program of research aimed to foster digital literacy capacities among youth and informal educators in the Greater Toronto Area (GTA) and specifically examined the extension of the Mozilla community’s free and open source software production practices to build a digital literacy network called Hive Toronto. This article presents results from a document analysis (n = 21) of applications, blogs, and other materials revealing how the people, challenge, practices, and results associated with social innovation unfolded through research with Hive Toronto. Based on these findings, the article demonstrates that tensions linger between industrial and social innovation funding, but that there is space for critical and activist research when building such partnerships.

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.

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
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 score0.671
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0020.004
Open science0.0030.000
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 head0.303
GPT teacher head0.424
Teacher spread0.120 · 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