Bibliographic record
Abstract
Purpose The purpose of this paper is to understand contemporary psychostimulant use among members of online discussion fora. Two objectives are addressed: to describe accounts of practices related to psychostimulant use, and to examine how these pharmaceuticals may shape contemporary subjectivities. Design/methodology/approach This paper presents a qualitative analysis of three online discussion fora belonging to Reddit. Drawing on actor-network theory, psychostimulants are envisaged as networked actants to understand the underlying logics related to their use. Non-participant observation of r/Adderall was carried out over an 18-month period. A qualitative analysis of postings on the three selected fora was also performed. Findings For each discussion forum, a network comprised of human and non-human actors was observed: members of the forum, psychostimulants as objects and subreddits as agentic spaces. This study reveals the emergence of multiple subjectivities associated with psychostimulant use: productivity, wellness and enhancement‐related. Practical implications Findings open to a wider debate regarding public health’s and healthcare professionals’ understanding of psychostimulant use outside of the clinical setting and how this may contrast with how psychostimulant use is practiced in context. Originality/value This research shows new online socio-cultural spaces formed around psychostimulant use. Calling upon a web-based ethnographic approach, this research presents a new perspective on the contemporary use of psychostimulants.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".