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Record W6993701063

Synergia Project

2014· other· en· W6993701063 on OpenAlexfundaboutno aff

Bibliographic record

VenueAUSpace (Athabasca University) · 2014
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersAthabasca University
KeywordsNucleofectionPretextArticular cartilage damageCircumstantial evidenceWork (physics)Frame (networking)
DOInot available

Abstract

fetched live from OpenAlex

The Synergia Project is a new initiative whose purpose is to promote online learning technology to support the diffusion of co-operative knowledge (both formal and tacit) and practice to meet the challenges of building a sustainable, equitable, and socially just future. A key aim of the project is to bridge the international co-operative movement with the emerging movement for a new commons and the global movement for sustainability.
\nHoused at the Athabasca University (AU) and supported by the participation of British Columbia-Alberta Social Economy Research Alliance (BALTA) in Canada, Co-operatives UK, Schumacher College, and the P2P Foundation, the project commenced in December 2013 with a dialogue process that engages key innovators and experts from the co-op, new commons and sustainability fields to participate in the design and content of an online learning platform using MOOC technology. The project is funded by the AU Research Fund.
\nThe completion of the program design and the confirmation of the MOOC content comprise Stage 1 of the project. Stage 2 entails the completion of the MOOC “curriculum” and the launch of the Synergia MOOC with links to concrete development opportunities on the ground.
\nThe project is being co-ordinated by Mike Gismondi at the Centre for Social Science at AU. John Restakis, Research Associate with Co-operatives UK and Research Investigator with the FLOK Project, is Lead Researcher for the Project and Pat Conaty, Research Associate with Co-operatives UK, is the Research Lead for the UK.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.025
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.031

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 head0.011
GPT teacher head0.214
Teacher spread0.203 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2014
Admission routes2
Has abstractyes

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