Dealing with Multiple Perceptions of 'Reality': Change Within a Transorganizational System
Bibliographic record
Abstract
Transorganizational systems (TSs) are defined as "coalition structures formed by two or more organizations for a common purpose" (Cummings, Blumenthal, & Greiner, 1983; p. 379).Although an extensive body of knowledge exists on TS outcomes, there has been little research exploring how TSs change over time.The thesis presents an exploratory, longitudinal, multi-method case study of a change initiative within a TS consisting of a police organization, a hospital, and a social service agency operating in a large city in Canada.The initiative involved the change to a process that is interdependently co-owned by all three organizations and relates to how these three partners deal with persons suspected of having mental illness in the community.Seventy-five semi-structured interviews (25 per organization) were conducted before and sixty semi-structured interviews (20 per organization) were conducted six months after the implementation of the planned TS change.The data from these interviews were supplemented with archival data from the police.We draw from planned change (e.g.Burnes, 2004), TS (e.g.Crosby, Bryson, & Stone, 2006), and stakeholder (e.g.Mitchel, Agle, & Wood, 1997) literatures to analyze findings from this thesis.The results of this thesis indicate that the planned TS change has had a measurable impact on the TS.The results also suggest that respondents' perceptions of what they wanted to change (pre-change) and what they observed had changed (post-change) in the TS influenced how they made sense of the planned TS change, and that these sensemaking processes affected their views of interorganizational relationships.Our analysis also suggests that the planned TS change:(1) shifted power within the TS from the hospital to the police, (2) shifted urgency within the TS from the police to the hospital, and (3) eroded the legitimacy of the police in the eyes of healthcare workers.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.029 |
| Scholarly communication | 0.020 | 0.022 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".