Quantity v/s quality of scientific publications: an analysis for main cities of Spain (2001-2007)
Bibliographic record
Abstract
Since the last quarter of the 20th century, most of the world population has experimented an important process of globalization, mainly due to; the accelerated knowledge production, the increase of intangible capital on a macroeconomic scale, the increase in levels of innovation, and the ICT revolution that have democratized access to information and knowledge dissemination. This new economic base, located in cities, is supported on knowledge and information as sources of production and competitiveness. The number of scientific publications on indexed journals is a scale, often used to measure the degree of strength of the scientific sector of a particular place. But this scale ignores the quality of the counted works, i.e. the impact they have generated in the scientific world. This work seeks to highlight the dynamics of scientific production in Spain. Specifically, it aims to analyze the quantity and quality of scientific publications in the period between 2001 and 2007. For this analysis, the quantity is measured by the number of scientific papers published by researchers from a city and the quality by the number of times that works signed by scientists from a city, have been cited by researchers around the world. In this study we establish a bibliometric analysis based on: 1) the number of scientific contributions to municipalities of more than 30,000 people whose information is derived from the SCI-E and 2) the number of citations for the top 10 cities with information derived from Scopus. Finally, we contrast the results of the more representatives cities, with the aim of clarify the relationship between the quantity and quality between quantity and quality of the scientific publication. The results suggest a concentration of quantity and quality of the scientific production in the Spanish metropolitan areas. However, we can provide that ranking who have the main cities in the context of national scientific publication is not similar for both parameters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.020 | 0.008 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.000 |
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 teacher head, 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".