Who are the users? Who are the developers? Webs of users and developers in the development process of a technical standard
Bibliographic record
Abstract
Abstract The paper presents an empirical study of user involvement in developing a technical standard for a scientific community's information system project. The case illustrates how multiple perspectives are involved when considering the user role in practice. The case presents a situation where both developers and users were pre‐defined in the design and development phases of the standard as homogeneous groups of actors. Groups of actors changed to become more heterogeneous and ‘fluid’ in the deployment and implementation phases, thus forming ‘webs of developers’ and ‘webs of users’. Detailed analysis of the process in its entirety shows the blurredness of boundaries between ‘developer’ and ‘user’ categories and roles, and reveals challenges at social and organizational levels. Three models pertaining to the system development process are presented in order to illuminate differing perspectives on the user and on the development process itself. The paper draws theoretically from information systems, social informatics, and science and technology studies. The research contributes to a deeper, interdisciplinary understanding of ‘the’ user, of multiple roles in systems development, and of dynamic sets of user–developer relations.
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 | 0.054 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.012 | 0.021 |
| Scholarly communication | 0.018 | 0.023 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".