Playing in the Sandbox: Considerations When Leading or Participating on a Multidisciplinary Research Team
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Research involves working to find answers to questions. Research questions of interest to pharmacists generally relate to any aspect of the discovery, effect, or use of medications, as well as the role of pharmacists within the health care system. This article describes the key aspects of leading or participating on a multidisciplinary research team so as to provide guidance to pharmacists involved in the research enterprise. The research questions that emerge from topics well suited to the expertise and experience of a pharmacist are often, by their inherent nature, best addressed by a team of people from different scientific backgrounds: individuals who can form a multidisci plinary team that will work together to develop and carry out all aspects of the research project. Although not all research questions require multidisciplinary research teams, it is beneficial to work as a team, with different perspectives, knowledge, and skills available to answer complex, multifaceted research questions. The team can integrate ideas across disciplines, advance thinking within and across disciplines, and go deeper and broader to create knowledge that can be used to develop novel, more meaningful solutions. Individual team members can also get to know new people (their fellow team members), achieve greater personal satisfaction, and have more fun along the way. Working as a team helps to improve knowledge translation of findings in multiple sectors, thereby increasing uptake and sustainability, and also creates wider networks and encourages development of professional relationships. Research funding agencies worldwide, including the
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it