Goal Orientation and Conflicts
Bibliographic record
Abstract
In this article we present parts of a larger research study, which aims at explaining how a process-oriented innovation unfolds and develops over time in Swedish health care. Through a longitudinal field study of a national and a local development project, we analyze how the flow model--a process-oriented innovation that emphasizes the sequence of activities a patient undertakes through the health care system--has been developed in Swedish health care. We propose to explain how the development projects unfold over time through the use of process theories of organizational development and change. The national project is best understood as a process of evolution from the phase of selection of projects and teleological (goal-oriented, socially constructed development) and dialectic theory (development via conflict of 2 opposing ideas from different organizational entities) through the process in which national ideas face real-world practice. We also propose a synthesis of dialectics and teleological motors for explaining local development. This synthesis proposes that local development teams have a rather broad notion of what it takes to implement the flow model. The team knows the goal, procedures, and activities from a broad perspective. Through a search-and-interact process, in which other organizational entities such as IT consultants, medical units and politicians have a heavy influence, the group sets and implements goals. Details of how to proceed are, however, constructed in the process of acting. This occurs as ideas are developed and tested in real settings. We conclude the article by presenting managerial implications for understanding these process patterns.
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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 | 0.018 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".