The Case for Information Brokering During Major Change: The Experience of the Transition Support Office of the McGill University Health Centre
Bibliographic record
Abstract
This paper describes the emergence of an "information brokerage" in the project management office of the McGill University Health Centre (MUHC) in Montreal. This process evolved during unprecedented transformation linked to a redevelopment project. Information brokering became a core function in the MUHC's context of major change. To develop an information brokering model, the paper draws upon the literature on knowledge brokering, applies Daft and Lengel's (1986) seminal framework on information processing in organizations, and builds on the MUHC experience. The paper proposes that knowledge brokering and information brokering are related, yet distinct in content, purpose and structure.
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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 | 0.021 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.035 | 0.036 |
| Scholarly communication | 0.026 | 0.013 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".