Action Learning and Reflective Practice in Project Environments that are Related to Leadership Development
Bibliographic record
Abstract
This article draws on the author's experience in attempting to facilitate the acquisition of reflective habits by individuals undergoing leadership development in business-related project environments. Notes that such communities accept only very practical interventions. Highlights the links between reflection and action learning. Clarifies how reflection and action learning are applied in the author's practice. Characterizes the action learning methodology used and contends that this approach forms a sound setting for reflective inquiry. Explains how the author informally embeds the principles of action learning in the project-related tasks of individuals undergoing leadership development. Describes a reflective learning framework and `tools' that are used by project participants to frame and facilitate the action learning processes. Explores the relevance of this action learning approach to building a learning organization and the development of leaders for such an organization. Gives particulars of a case study to confirm that these various elements can be successfully woven together in a real-life leadership development initiative.
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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 | 0.022 | 0.066 |
| 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 | 0.026 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".