Students' inventory of social actors concerned by the controversy surrounding cellular telephones: A case study
Bibliographic record
Abstract
Abstract The present article scrutinizes the manner with which a group of three postsecondary students (in Quebec, Canada) describe the social actors concerned by the controversy surrounding cellular telephones. The study was conducted on the basis of an ethnographic approach. Participant observation was performed by the researcher for 3 hours during each of 15 weeks. The theoretical framework developed by Callon, Lascoumes, and Barthe (2001) was drawn on to show how the group assigns roles relating to public representation and the production of legitimate knowledges; in particular, it assigns to scientists the role of conducting research; to government the roles of building citizens' awareness about the risks related to cellular telephone use, protecting users, and guiding the conduct of the cellular telephone industry; and to citizens the roles of becoming/staying informed and of making limited use of cellular telephones. The study reported here also illustrates that, in the process, the group airs their views concerning the terms best suited to defining the subject of the controversy, constituting research “collectives,” and disseminating knowledge. One main conclusion is that science education research projects drawing on the contributions of Callon et al. (2001) hold out considerable promise in terms of relevance and fruitfulness. © 2008 Wiley Periodicals, Inc. Sci Ed 92:543–559, 2008
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".