Elementos clave para la introducción de la perspectiva de género en las infraestructuras ciclistas
Bibliographic record
Abstract
Gender mainstreaming generated a wide diversity of innovative measures and interventions in new areas not explored until the moment. This is the case of mobility policies, linked to the sustainable urban design and the measures for the environment’s improvement. The literature review and the analysis of the cities’ experiences, allow us to establish some criteria to audit the level of inclusivity of transport infrastructures. In the case of cycling infrastructures, the following criteria have to be taken into account: security, ensuring road safety elements and adequate lighting; conciliation, connecting areas of the city linked to child care, elderly care, daily shopping and personal dealings, through Geographic Information System (GIS) analysis; apply an inclusive and participatory approach, from the comprehension that there is a diverse citizenship with multiple needs and that these have to be taken into account during the design of these policies; and the visibility of cyclist women, as a tool of empowerment and promotion of the use of the bicycle..
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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 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".