Building Business Relationships Through the Web: How Medical Technology Companies Enroll Stakeholders in Innovation Development and Uptake
Bibliographic record
Abstract
Abstract: Websites are perceived as an additional communication space where public and private institutions and their stakeholders can interact and develop sustainable relationships. Although public relations scholars argue that both companies and consumers may benefit from virtual interactions, the growing online direct-to-consumer advertising and sale of health-related products has raised social and ethical concerns. Our study seeks to clarify the scope and nature of the virtual relationships that are specific to medical devices companies. Through a qualitative analysis of website, we show how four Canadian medical technology companies sought to enroll three types of stakeholders into their innovation development and commercialization strategies: investors, healthcare providers and patients. Our findings show that by reinforcing stereotypical relationships with investors, the websites maintain certain disconnect between the worlds of business and healthcare, and by creating proactive roles for healthcare providers and patients, they contribute to forge ethically convoluted relationships.
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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 | 0.022 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.013 |
| Scholarly communication | 0.018 | 0.014 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".