Butcher, Neil (2011) A basic guide to open educational resources Commonwealth of learning (Vancouver) <scp>isbn</scp> 978‐1‐894975‐41‐4 133 pp CDN$12 (free download) http://www.col.org/resources/publications/Pages/detail.aspx?PID=357 <b>Commonwealth of learning</b> (2011) Guidelines for open educational resources in higher educationCommonwealth of learning (Vancouver) <scp>isbn</scp> 978‐1‐894975‐42‐1 22 pp + dvd CDN$12 (free download) http://www.col.org/resources/publications/Pages/detail.aspx?PID=364
Bibliographic record
Abstract
Summary A basic guide to open educational resources ( oer ) and Guidelines for open educational resources in higher education are two slim volumes that provide a detailed, succinct and immensely valuable overview of oer policy and practice that should be useful across all sectors of education, from schools to universities. If these books are relevant to you, I recommend you download or buy copies. M ichael T homas
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.194 | 0.201 |
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".