Annual report 2017-2018 of the chair UNESCO e ICDE: Open educational movement for Latin America
Bibliographic record
Abstract
With the general objective of promoting the integration of research, training, and documentation of the open educational movement in Latin America, we worked based on the specific objectives, where the following results were achieved: \n\tObjective 1. To share and mobilize open knowledge, through training processes and implementation mechanisms. \nResults 17 lectures, 11 MOOCs (in the open platforms MexicoX and EdX), 8 workshops and 1 OpenLab were given, impacting more than 50,000 people from more than 40 countries. \n\tObjective 2. To promote the integration of academics from Latin America, through collaborative networks, to use and produce OER and join efforts to reduce gaps in education. Results The "UNESCO / ICDE International Stay 2017 Open Educational Movement for Latin America" was held from December 1 to 15, 2017, in Monterrey, Mexico (http://hdl.handle.net/11285/627991). 82 attendees from 11 countries participated: Argentina, Costa Rica, Chile, Colombia, Ecuador, Guatemala, Mexico, Peru, Paraguay, United Kingdom and Venezuela, as well as 18 panelists from Spain, Hong Kong, England, and Mexico. \n\tObjective 3. To produce and disseminate studies of the open educational movement and promote practices of digital publications. \nResults Three studies were carried out with funding from CONACYT and the Ministry of Energy of Mexico, 20 articles, 8 conference papers, 3 edited books and 101 open educational resources were published, available in open access at the Tecnologico de Monterrey repository (https://repositorio.itesm.mx/discover?scope=%2F&query=266632&submit=) \n\tObjective 4. To promote cooperation with other UNESCO Chairs in the area of open educational resources. \nResults Participation with the UNESCO Chair of the University of Athabasca, Rory McGreal, in the thematic edition of the Monograph for the Journal Comunicar (JCR Magazine and Scopus Q1) with the theme: "Science and shared knowledge. Open access, technologies, and education." (https://www.revistacomunicar.com/index.php?contenido=revista&numero=54). Additionally, we participated in 2 panels with other UNESCO Chairs at the conferences of Canada and Slovenia and with the UNESCO Ecuador Office to give a lecture on inclusion. \n\tObjective 5. To cooperate closely with UNESCO in other relevant programs and activities. Results We were actively involved in the "OER Action Plan of Ljubljana", which was the product of a worldwide open consultation process - 6 regional consultations, open online consultation and debate during the 2nd OER World Congress, held on September 18-20, 2017 in Ljubljana, Slovenia, with more than 500 stakeholders from all regions, including 14 Ministers of Education or Higher Education.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.085 | 0.033 |
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".