Opening Up The Tools For Doing Science: The Case Of The Global Open Science Hardware Movement
Bibliographic record
Abstract
Open science hardware (OSH) is a term frequently used to refer to artifacts, but also to a practice, a discipline and a collective of people worldwide pushing for open access to the design of tools to produce scientific knowledge. The Global Open Science Hardware (GOSH) movement gathers actors from academia, education, the private sector and civil society advocating for OSH to be ubiquitous by 2025. This paper examines the GOSH movement’s emergence and main features through the lens of transitions theory and the grassroots innovation movements framework. GOSH is here described embedded in the context of the wider open hardware movement and analyzed in terms of framings that inform it, spaces opened up for action and strategies developed to open them. It is expected that this approach provides insights on niche development in the particular case of transitions towards more plural and democratic sociotechnical systems.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.027 | 0.058 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.009 | 0.007 |
| 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".