Bibliographic record
Abstract
The idea of this special issue originated from the 2015 annual conference of the US Comparative and International Education Society (cies) that was held in Washington, DC, under the theme of "uBuntu!Imagining a Humanist Education Globally" (https://convention2.allacademic.com/one/cies/cies15/).Professor N'Dri Assié-Lumumba organized this conference in her capacity as the incoming President of cies, working in close collaboration with Dr. Joan Osa Oviawe, who was a visiting scholar at Cornell University and served as the conference planning chair.One of the innovative features of the conference was the invitation made to several cies members to respond to the theme from regional or thematic perspectives which were included in the program and contributed to elicit more interest before, during and since the conference.Invited to be a keynote speaker at the Conference, Professor Samir Amin delivered by teleconference his address titled "The Question of Education, Science and Technology in the Contemporary Time: On the Theory of Cognitive Capitalism."As a global icon, his presentation electrified the audience.On the whole, the conference stirred considerable interest and enthusiasm.It was attended by more than 3300 participants from more than 100 countries.Professor Assié-Lumumba and Dr. Oviawe, along with several other colleagues, discussed the importance of producing post-conference publications in various outlets to continue the insightful deliberations on the uBuntu paradigm.This special issue is one of such publications, some of which came out in 2017 and 2018.It is the result of Professor Assié-Lumumba's enthusiastic response to the invitation of Dr. Pak Nung Wong, Editor-in-Chief of Bandung: Journal of the Global South, to produce a special issue titled "uBuntu, World Epistemologies, and Humanist Education."She asked Dr.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.775 | 0.728 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".