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Record W4399709859 · doi:10.14742/apubs.2015.987

Community volunteers in collaborative OER development

2015· article· en· W4399709859 on OpenAlexaff
Irwin DeVries

Bibliographic record

VenueASCILITE Publications · 2015
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsCommunity developmentEconomic growthEconomics

Abstract

fetched live from OpenAlex

The purpose of this comparative case study is to explore and examine the practices of open course design and development community volunteers undertaken in the Open Education Resource universitas (OERu) network, an international partnership of member post-secondary institutions. With a focus on the design and development of an OER-based university-level course, the study identifies and describes features of an OERu open design and development volunteer community and compares and contrasts it to a similar community in the free and open source software (FOSS) development field.

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)0.029
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.042
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0130.010
Scholarly communication0.0060.004
Open science0.0030.016
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.051
GPT teacher head0.306
Teacher spread0.255 · 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.

Study designQualitative
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
Published2015
Admission routes1
Has abstractyes

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