Historiography taking issue, analyzing an experiment with heroin maintenance.
Bibliographic record
Abstract
This article discusses the predicament of historians becoming part of the history they are in-vestigating and illustrates the issue in a particular case. The case is that of the randomized controlled trial (RCT)—more specifically, its use for testing the effects of providing heroin to severe heroin abusers. I counter the established view of the RCT as a matter of timeless logic and argue that this research design was developed in the context of administrative knowledge making under twentieth-century economic liberalism of which it epitomizes some central values. I also argue that the applicability of the RCT depends on the degree to which its advocates can define the issue to be studied according to its inherent values. Next, I demonstrate how advocates of an RCT with heroin provision in the Netherlands steered the political discussion on heroin provision and how the values of economic liberalism also shaped the results of the Dutch maintenance experiment. In addition, I relate how my analy-sis of this experiment became part of political debates in the Netherlands. Contrary to my intentions, adversaries of heroin maintenance used my critique on the heroin RCT as an ar-gument against heroin maintenance. Such risks are inherent to historiography and sociology of science aiming at practical relevance while challenging treasured scientific beliefs. I con-clude that it still seems better to expose arguments on unjustified certainties than to sup-press them for strategic reasons. © 2004 Wiley Periodicals, Inc. Various European countries and Canada are currently conducting or planning scientific experiments with the provision of heroin to severe heroin abusers. The intention is to find out whether or not free heroin improves the physical and mental condition of despondent users and diminishes the nuisance often caused by them.
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 | 0.035 | 0.066 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 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".