Problematizing the user in user-centered production: A new media lab meets its audiences
Bibliographic record
Abstract
With the widespread implementation of ‘participatory’, ‘user-led’, and ‘user-centered’ principles in both the practice and study of technology production, it has become commonplace to treat users as partners in design. This paper is critical of that trend, arguing that the users of a technology in development must first be treated as objects rather than agents of social construction. It draws from a case study of a publicly funded British production-research laboratory in educational new media that was carried out during its first year of existence. The case study highlights some of the tensions and contradictions between the discourse and practice of user-centered design during an uncertain period in a project. By extending Callon’s concept of problematization to include the putative users of technologies in development, this study shows how producers distinguish and mediate between users and partners; how they sustain the notion that there is a group of users ‘out there’ whose existence and requirements can be substantiated prior to the creation of specific technical choices; and how user involvement in and of itself is used for the strategic purpose of enticing partners and asserting their control over the production process. By doing so, the paper affords insight into the practitioners’ belief in the need to gain ever more refined knowledge of specific users, and their recourse to their own experience as a necessary alternative.
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 | 0.052 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.022 | 0.059 |
| Scholarly communication | 0.030 | 0.039 |
| Open science | 0.003 | 0.026 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".