Scientific infrastructure design: Information environments and knowledge provinces
Bibliographic record
Abstract
Abstract Conceptual models and design processes shape the practice of information infrastructure building in the sciences. We consider two distinct perspectives: (i) a cyber view of disintermediation where information technology enables data flow from the ‘field’ and on to the digital doorstep of the general end‐user, and (ii) an intermediated view with bidirectional communications where local participants act as mediators within an information environment. Drawing from the literatures of information systems and science studies, we argue that differences in conceptual models have critical implications for users and their working environments. While the cyber view is receiving a lot of attention in current scientific efforts, highlighting the multiplicity of knowledge provinces with their respective worldviews opens up understandings of sociotechnical design processes and of knowledge work. The concept of a range of knowledge provinces enables description of dynamic configurations with shifting boundaries and supports planning for a diversity of arrangements across the digital landscape.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.016 | 0.016 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".