Action learning: towards a framework in inter-organisational settings
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
While much of the literature on action learning focuses on managers developing their capacity to learn and transform their own organizations, this article explores how action learning has been used in inter-organisational settings. Two settings are presented: the first an EU-funded management development programme called the National Action Learning Programme (NALP) which ran in Ireland from 1998 to 2000 and the second an EU funded programme, called CO-IMPROVE which commenced in March 2001 and involves inter-organisational networks in three European countries. The essential structure of the NALP approach—the action learning approach and the inter-organisational learning network—has been adopted in CO-IMPROVE. The need here for a well-developed capacity to learn, not only at the levels of individuals or companies, but also at the inter-organisational (or extended manufacturing enterprise (EME)) level required the application of an action learning approach. The application of NALP in such a new and wider organisational setting has promised two potentially desirable outcomes: the rapid facilitation of the particular needs of the CO-IMPROVE research project and the further development of the approach itself. The article describes the two programmes and reflects on (a) the action learning processes in inter-organisational settings, and (b) the outcomes with respect to management and organisational learning that point to ways in which the exciting field of inter-organisational action learning may be developed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.012 |
| 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 | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it