Interconnected influence: Unraveling purdue pharmaceutical's role in the global response to the opioid crisis
Bibliographic record
Abstract
BACKGROUND: The global pharmaceutical industry has a long history of prioritizing profits over public health through widespread practices such as price gouging, deceptive marketing, and fraud. A prominent example of this issue is the mislabeling and mass-marketing of OxyContin by Purdue Pharmaceuticals (Purdue) that catalyzed the opioid crises in and beyond the United States. METHODS: Guided by Actor-Network Theory, this case study employs Visual Network Analysis to map the actors-networks involved in responding to the harms caused by Purdue. Data was generated from peer-reviewed and grey literature published between 2007 and 2022 (n = 40) and imported into Gephi visualization software where centrality metrics were applied. RESULTS: A total of 39 actors and 99 relationships were visualized based on the relational thinking that actors who are heavily interconnected with others are rendered important. Centrality measures identified the socio-technical centrality of Purdue in influencing the response to the harms it caused. Purdue exerted influence through various avenues, most prominently through the creation and cooptation of pain advocacy groups, their close ties with United States elected officials, and through embedding pro-opioid messaging in international guidance documents. In doing so, Purdue was able to extend the reach and impact of their opioid promotion, while simultaneously limiting the capacity of regulatory bodies to pursue accountability and implement policies to mitigate opioid-related harms. CONCLUSION: This study advances understandings of the complex interplay between transnational pharmaceutical companies, global health systems, regulatory bodies, and public health. In doing so, we underscore the need for stronger regulation and increased transparency surrounding the interactions between pharma, patient groups, governments, and international organizations to better address and prevent future harms.
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".