Scientometric analysis of research from a feminist perspective.
Bibliographic record
Abstract
In order to build a historical map of scientific production from a feminist perspective and to analyze the central themes that have been studied by the academics from this approach, a search was conducted using SCOPUS an international bibliometric database, for the period between 1960 and July 2013. The search strategy based on the use of four key words produced 54 articles, written by 86 specialists of 14 countries, among them USA, UK, Canada and Australia, 87% written in English and 4% in Spanish. Even though the feminist theoretical approach is interdisciplinary by definition, the main disciplines represented in the sample were social sciences and Psychology. 69% of the articles were written by a single author, and 78% of the authors were women. Citation varied between 137 and zero. The most cited studies were from Canada, USA and the UK. Articles covered a wide variety of themes emphasizing theoretical, methodological and empirical issues in different areas of knowledge. Additionally a very low presence of articles dealing with the impact of the feminist perspective in public policies was observed, as well as very few articles devoted to examine applications of the feminist theory on education. Conclusions highlight the challenge for Latin American feminist researchers to increase their presence in scientific journals with international distribution indexed in SCOPUS, and to increase the quality of specialized Hispanic journals, in order to favor scientific dissemination on the subject in Spanish.
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 | 0.046 | 0.206 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.227 | 0.298 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".