International Collaborations: Librarians Without Borders and Librii inGhana
Bibliographic record
Abstract
In 2011, Librarians Without Borders began a partnership with Librii to assist this fellow nonprofit organization with developing its vision of building a Carnegie-inspired model of libraries across Africa. Librarians Without Borders (LWB), founded in February 2005 at the University of Western Ontario, is a nonprofit organization that strives to improve access to information resources regardless of language, geography, or religion, by forming partnerships with community organizations in developing regions. Powered by student committees at five Canadian universities and a volunteer Executive Team and Board of Directors, LWB’s vision is to build sustainable libraries, support librarians, and use librarian know-how to drive lasting and sustainable development of information resources around the world. Librii is a subsidiary of Libraries Across Africa, founded in 2010 with roots at Rice University in Texas. Librii’s vision is to work with communities to build a network of low-cost, digitally powered libraries deployed along the expanding fiber-optic infrastructure in the developing world.
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 | 0.025 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.036 | 0.015 |
| Scholarly communication | 0.035 | 0.027 |
| Open science | 0.002 | 0.034 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.025 | 0.005 |
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".