Bibliographic record
Abstract
This dissertation is a study in rethinking the phenomenon of polypharmacy, reconceptualizing it as practice. Conventional research in polypharmacy and medication work has failed to consider conceptions of power, situated and collective knowing, and key roles of the body, materials, and discursive practices. Drawing on ethnographic research in a Canadian long term care facility, I trace everyday organizational routines that are integral to the prefigurative practice-arrangement of the work of doing polypharmacy. My observational research, focussing on the bi-annual medication review and the medication reconciliation process, illustrates how practitioners and residents engaged in the broad range of medication work, talk and act in ways that are dissimilar to the conventional literature.The practice of polypharmacy has intended and unintended impacts and power effects on practitioners and residents. I illustrate how sociomaterial elements such as bodily sayings and doings, space, and objects pattern the world of the long-term care organization. I explore the tangled work on residential floors and show how humans and non-humans are relationally implicated in the production and reproduction of maintaining the organizational flow of medications. I describe the work of polypharmacy that keeps residents and practitioners dependent on each other as the residents require medications and practitioners engage in paid medico-legal work. One significant effect is that vulnerable residents are largely excluded from polypharmacy related decision-making while, at the same time, accepted routines impose on them a significant burden of treatment. My research challenges and then extends our real-world understanding of polypharmacy. It exemplifies how everyone, and everything is engaged in doing the institutional work of polypharmacy. My work argues for recognizing polypharmacy as practice. In so doing, I recast polypharmacy from an individual, cognitive, and decontextualized activity to one that recognizes it as a sociomaterial, distributed, and complex routinized institutional practice. The work of polypharmacy is a ‘boring’ yet powerful routine. This new understanding comes with a fresh vocabulary, novel ways of thinking and brand-new questions to be asked. I propose that this new way of understanding the institutional work of polypharmacy and medication work has significant consequences for research, medical practice and education programs.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.026 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".