Exploration of open educational resources in non-English speaking communities
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.
Bibliographic record
Abstract
<p>Over the last decade, open educational resources (OER) initiatives have created new possibilities for knowledge-sharing practices. This research examines how, where, and when OER are attracting attention in the higher education sector and explores to what extent the OER discussion has moved beyond the English-speaking world. This study analysed English, Spanish, and Portuguese OER queries over a long-term period (2007-2011). The data retrieval was conducted using four online platforms: two academic journal databases (Web of Knowledge and Scopus), one video-sharing Web site (YouTube), and one document-sharing Web site (Scribd). The number (more than 32,860) of search results collected indicate an increasing interest in online OER discussion across languages, particularly outside academic journal databases. Additionally, a widening ‘language gap’ between OER discussions in English and other languages was identified in several platforms. This research reports some of the cultural and language challenges caused by the expansion of the OER discussion and highlights relevant findings in this field.</p>
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it