Developing guiding principles: an organizational learning perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose Guiding principles are knowledge structures that call to mind collective narratives with emotional content, and are articulated and used heuristically to guide decision making in organizations. The purpose of this paper is to explore how: guiding principles become integrated in management teams through discursive processes of social learning, and how process techniques from the realm of organizational learning can be used to facilitate the development of guiding principles. Design/methodology/approach Develops theoretical findings drawing from the organizational learning literature, and explores these findings through use of a two‐part illustrative case study of guiding principles development in a European telecommunications firm. Findings It was found that guiding principle development may be facilitated using process techniques similar to those proposed for integrating organizational learning, namely, a dialogue‐intensive process involving stages of inquiry, divergence and convergence. Research limitations/implications The study focuses on dialogue, while future studies may usefully focus on non‐discursive aspects of the conversational setting and structure in which the empirical case was embedded. Originality/value This paper combines both theory development with illustrative empirical data to shed light on the process by which guiding principles may be intentionally developed in an organizational setting.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it