Bibliographic record
Abstract
Current research provides little insight about how space and coordination are mutually shaping. The influence of space and spatial configuration is especially important in knowledge settings where work is built around material arrangements such as space, objects, bodies and things-in-use. This paper investigates how expertise coordination unfolds when work implicates space in a significant way and space is dramatically altered. To answer this research question, we undertake a 14 month ethnography (currently on-going) that involves the merger and relocation of two neonatal intensive care units in Canada’s largest health system network. In this setting, two groups of clinical staff with complementary expertise and differing baby populations are brought together in a radically altered physical layout of a newly built super hospital facility. We find that space can reconfigure task dependencies and uncertainties while hindering expertise integration. These complications trigger planned and/or improvised organizational responses each with unforeseen consequences. The resultant interplay of unanticipated influences, organizing consequences and in-situ responses results in a messy unfolding coordination trajectory. This complex trajectory continues to expose new ways of organizing that emerge over time.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.032 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".