Characterizing UNAM’s Open Education System Using the OOFAT Model
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
Mexico’s national university (UNAM) is a public mega university with a 46-year history in open education. This article presents an analysis based on the open, online, flexible provision of technology-enhanced higher education (OOFAT) model, developed by Orr and his colleagues (2018). The aim of this analysis was to characterize UNAM’s open and distance education system in terms of openness, flexibility, and its business model, in three distinct time periods. According to this analysis, the system has evolved in all areas, and at present has a content-focused approach in terms of flexibility and openness, which differs from the OOFAT at the center approach that is desired. The study also characterized the UNAM system’s business model as a prospector-like approach, which highlights the possibilities for instilling innovation through the schools that comprise this system. The analysis allowed for mapping the current situation and thus sheds light on defining the steps necessary for creating an integrally open system.
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 | 0.008 | 0.000 |
| 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 | 0.001 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| 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