Dealing with real-life laboratories in energy research : the power of the experimenter
Bibliographic record
Abstract
Following the theoretical approach developed by Herbold (1995), Gross and Krohn (2005), and Van de Poel et al. (2017), this paper focuses on an on-going social experiment that remains a sensitive challenge for the future of nuclear energy research: the radioactive waste management. More specifically, this paper scrutinizes and compares the attitude of three nuclear waste management organizations (considered here as the experimenter) during the on-going implementation of high-tech waste disposal. Based on 82 semi-directive interviews conducted in Belgium, in France and in Canada, this paper intends to empirically highlight how the experimenter bound to participate in complex networks and unable to completely control the experimental process develops two different attitudes (“open” or “closed” experimental mindset). We sustain that those attitudes produce different public engagements (empowerment or resistance). Particularly, the initiator of the social experiment should adopt an “open” experimental attitude regarding his multiple audiences in order to sustainably deal with uncertainties of decision-making processes related to nuclear energy issues and more globally, energy transition ones. Gross, Matthias, and Wolfgang Krohn. “Society as Experiment: Sociological Foundations for a Self-Experimental Society.” History of the Human Sciences 18 (2005): 63–86. Herbold, Ralf. “Technologies as Social Experiments. The Construction and Implementation of High-Tech Waste Disposal Site.” In Managing Technology in Society. The Approach of Constructive Technology Assessment, edited by Arie Rip, J. Thomas Misa, and Johan Schot, 361. London and New York: Pinter, 1995. Poel, Ibo van de, Lotte Asveld, and Donna C. Mehos. New Perspectives on Technology in Society: Experimentation Beyond the Laboratory. Routledge, 2017.
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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 | 0.216 | 0.241 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.085 |
| Scholarly communication | 0.013 | 0.020 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".