Science, technology and Solidarity
Bibliographic record
Abstract
Science and technology are changing. We have seen the emergence of open and citizen-based science practices in the context of facing pandemics, such as COVID-19, xenophobia, or inequality, among others. Open science is a movement that advocates the collective construction of knowledge. This perspective has shown its importance with the emergence of rapid response initiatives to the current situation at national and international levels. This article discusses the relevance of knowledge commons and transparent objects in the era of intellectual property. Solidarity technoscientific initiatives become a vehicle to pose free culture as a pillar of a human future based on mutual support. In that sense, universities, publishers, students, the scientific and engineering community, and even citizens are creating efforts around open science intending to share results, data, designs, specifications, and even resources despite new socio-political limits and precautions. We argue that a technoscientific movement based on solidarity, free and open culture, is key to permeate and transform the various layers of governments, research institutions, and citizens-led initiatives. To address this, several examples are exposed offering a brief critical appraisal in the context of open science, a concept still in the making.
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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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.015 | 0.136 |
| Scholarly communication | 0.022 | 0.023 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".