The IDRC Digital Library: An Open Access Institutional Repository Disseminating the Research Results of Developing World Researchers
Bibliographic record
Abstract
The International Development Research Centre (IDRC) has recently launched the OAI-PMH compliant IDRC Digital Library (IDL), a DSpace institutional repository. The digital library has been developed to enhance the dissemination of research outputs created as a result of Centre-funded research. The repository has a number of unique qualities. It is the public bibliographic database of a Canadian research funding organization, its subject focus is international development and the content is retrospective, dating back to the early 1970s. Intellectual property issues have been a major factor in the development of the repository. Copyright ownership of a majority of IDL content is held by developing world institutions and researchers. The digitization of content and its placement in the open access IDL has involved obtaining permissions from hundreds of copyright holders located in Africa, Asia and Latin America. IDRC has determined that obtaining permissions and populating the repository with developing world researchers’ outputs will help to improve scholarly communication mechanisms for Southern researchers. The expectation is that the IDL will make a contribution to bridging the South to South and South to North knowledge gap. The IDRC Digital Library will serve as a dissemination channel that will improve the visibility, accessibility and research impact of southern research.
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 | 0.011 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.019 | 0.042 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.029 | 0.010 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.267 | 0.160 |
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".