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
Abstract This chapter considers some of the challenges of the development of strategy, both for the conventional and ODDE sectors of higher education, with a brief look at the literature since strategic planning was first in vogue in the private sector in the early 1960s. Although the most common approach in higher education, so much so-called strategic planning does little to advance long-term visions and strategies or to differentiate one institution from another. The sudden pivot to online learning and other distance education that the COVID-19 pandemic has forced on conventional (contact) institutions has blurred distinctions between traditional and ODDE universities, thus rendering effective strategy development and implementation more important than ever. This chapter conducts the literature review considering both institutional and system-wide strategy development, underlining their common elements. Then, from the unique vantage point of the South African Institute of Distance Education ( Saide ), a nongovernmental organization based in Johannesburg but conducting projects throughout South Africa and sub-Saharan Africa, it discusses the challenges for ODDE strategy development in the particular context of COVID-19. The chapter concludes with implications from the analysis for both the conventional and ODDE sectors in higher education in South Africa and elsewhere based, in part, on the lessons learned during the pandemic.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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