McGreal, R. (2017). Special Report on the Role of Open Educational Resources in Supporting the Sustainable Development Goal 4: Quality Education Challenges and Opportunities
Bibliographic record
Abstract
Open Educational Resources (OER) and their offspring, Massive Open Online Courses (MOOCs), are becoming important factors in achieving the Sustainable Development Goal 4: Quality Education (SDG4). This was recognised early on by UNESCO in 2004 when they first coined the term "Open Educational Resources" and in 2012 with the OER Paris Declaration. UNESCO is continuing its support of OER with the 2nd OER Summit in September 2017. There is recognition that OER and MOOCs, while not being the solution to the world's educational crises, will play an important, if not essential, role. The OER movement is less than 15 years old and is growing rapidly as more and more nations and institutions adopt the view that publicly-funded research and educational content belongs to the people and should therefore be open and accessible to them. Canada can play an important role in supporting SDG4 by increasing its support for OER and open education in general, both in Canada and abroad.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.035 | 0.020 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".