Revue Réflexions Juridiques Africaines
Bibliographic record
Abstract
Revue Réflexions Juridiques Africaines, RJA in acronym, is a scientific journal, paper and electronic version, focused on the dissemination of research in law and interdisciplinarity.It is a bilingual publication space (French and English) that is both rigorous and accessible, offering researchers and thinkers in law and interdisciplinarity essential visibility for their personal, professional and academic development. It offers its authors excellent exposure since its content is broadcast and distributed in paper format and in electronic format on its website and other platforms.The quality of its publications is due to the rigor in the evaluations by professors, experts and researchers of high scientific quality, both national and international, of the texts submitted to it. The vision is to be a reliable and regular publication space for the influence of its authors who are researchers from different national, African and international universities. The Review thus hopes to inspire vocations, but also to raise awareness among researchers (from the university circuit or not) from the Democratic Republic of Congo (DRC) and around the world to the importance of the doctrine, a cornerstone and fundamental source in law, as well as the way in which it is constructed. Doctrine and jurisprudence being evolving and dynamic sources of law.
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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| 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".