Bibliographic record
Abstract
Do basic scientists and clinicians represent two separate sub-cultures? In other words, if culture is defined from a cognitive perspective, do basic scientists and clinicians espouse similar beliefs and understandings about the objects and events in the world around them? What are the differences and similarities between scientists and clinicians? How do they relate to common objects? This research is a case study of basic scientists and clinicians working in the areas of Magnetic Resonance Imaging (MRI) and Multiple Sclerosis (MS) in a Western Canadian university hospital. Based on five months of qualitative and quantitative fieldwork, this study indicates that there are differences in how basic scientists and clinicians perceive five shared boundary objects: the MRI, the neurological patient, the CNS disease, neurological diagnosis, and the brain. This research also describes the social life of MRI as it passes through sub-cultures within a hospital organization.
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 | 0.016 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.038 | 0.062 |
| Scholarly communication | 0.029 | 0.011 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".