The War of the Woods: Facilitators and Impediments of Organizational Learning Processes
Bibliographic record
Abstract
This study examines unfolding organizational learning processes at MacMillan Bloedel, a company which, after years of resisting stakeholder pressures for change, disengaged from the field’s dominant paradigm and developed a new solution. We elaborate the Crossan, Lane and White multi–level framework of organizational learning processes, finding support for the four feedforward learning processes they identified (intuiting, interpreting, integrating and institutionalizing), and adding two action–based learning processes: ‘attending’ and ‘experimenting’. We introduce the concept of a ‘legitimacy trap’ to describe an organization’s over–reliance on institutionalized knowledge when external challenges arise. The trapped organization rejects external challenges of its legitimacy when it perceives the sources of those challenges to be illegitimate. Feedforward learning is blocked as the organization escalates its commitment to its institutionalized interpretations and actions. Taking a grounded theory approach, we discuss how individuals attend to new stimuli and engage in intuiting about them, how groups interpret, experiment with and integrate new solutions, and how the firm validates and institutionalizes the successful solution. Facilitators and impediments of each of these learning processes are identified. Our additions to the model recognize the importance of context in organizational learning processes, and suggest how power may impact organizational learning.
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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 | 0.019 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| 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".