Estado de la investigación en la Universidad Nacional
Bibliographic record
Abstract
This report is made at the request of MSc. Daniel Rueda, Vice Rector for Research, who expressed his interest in having a diagnosis of research at the Universidad Nacional (UNA) during the five-year period 2015 - March 2020, hereinafter period 2015 - 2020. With this purpose, as a reference of the external context of the institution, in section 2, National and inter-university context, a brief description of research at the national level and of the State University Higher Education Institutions (IESUE) is presented, which takes as a reference the reports published by the Ministry of Science, Technology and Telecommunications (Micitt) and the National Council of Rectors (Conare) - Subcommission of Research Indicators. Also included in this document is information contained in other work that was prepared during 2019 and the first quarter of 2020 in the Vice Rector's Office for Research, in coordination and under the framework of the Quality Management System for Institutional Excellence (Sigei) initiative. In addition, section 4, Input indicators for research in the UNA, analyzes the investment indicators that, based on the results of the institutional budget execution of the previous year, the team of the Academic Information System (SIA) builds and sends yearly, for their integration, to the Micitt and the Office of Higher Education Planning (OPES) - Conare. In addition, SIA reports were generated that made it possible to construct and present indicators related to the personnel assigned to research Programs, Projects and Activities (PPAA) that were in force in one or more years of the period. The SIA was used as a reference because it is considered that the information contained in this platform better reflects the allocation of human resources to the work of the PPAA than the staff appointment platforms themselves; a study conducted in 2019 in the Office of the Vice Rector for Research confirmed this. In addition, the assignments registered in the SIA are supported by approval agreements, endorsements and endorsements from the corresponding councils and vice rector's offices. Section 5, Research programs, projects and activities, is also based on the information contained in the SIA. Reports were generated for the PPAA, whose data were evaluated and updated based on the institution's budget structure standard, which defines the budget programs, subprograms and characteristics of academic activities based on the definitions contained in the Regulations for the Management of Academic Programs, Projects and Activities (PPAA) and in the Frascati Manual for the measurement of scientific, technological and innovation activities; both were in force when the institution's budget structure was defined in 2007. Section 6, Academic production, presents two types of information, the first related to the institution's academic scientific journals, in which some of the results of the institution's own academic work and that of other national and international organizations are published. The other information is related to publications of our staff in robust indexes such as Web of Science and Scopus, as well as in the institutional scientific-academic journals and in the Institutional Academic Repository (RAI). This document closes with a section of conclusions and recommendations to improve research management at the institutional level. It is important to point out that one of the limitations of this report is the absence of information related to research laboratories; this is due to the fact that there is no complete record of them as academic programs. Only 45 laboratories were registered during the period, 30 from the Faculty of Exact and Natural Sciences and 15 from the Faculty of Earth and Marine Sciences.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.074 | 0.023 |
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".