Leading with two eyes: leadership failures and possibilities in the management of a pulp mill’s wicked problem
Bibliographic record
Abstract
Purpose The motivation for this paper comes from Canada’s Truth and Reconciliation’s (TRC) Calls to Action, and in particular, the call for more meaningful consultation and respectful, consent-based relationships between businesses and Indigenous communities in Canada. To this end, this study empirically examines leadership in the context of a wicked problem faced by a pulp and paper mill and suggest an Indigenous epistemology as helpful to inform the leadership behaviours employed in this company. Design/methodology/approach Firstly, this study established that the problem faced by the company aligns with the characteristics of wicked problems, hence necessitating a collective leadership approach. This study then compiled a database from publicly available documents and inductively coded this data to identify themes that told us something about the leadership behaviours employed by the company as it attempted to resolve the problem at hand. Findings This study provides evidence that the company did not employ collective leadership when attempting to tame its wicked problem. It then shows that the context in which the firm operates lends itself well to the Mi’kmaw concept of Two-Eyed Seeing as a guiding principle that could have informed the company’s leadership and contributed to a long-overdue process of reconciliation. This study proposes several specific actions that plausibly could have helped produce such an outcome. Originality/value This paper helps fill a void in applications of the wicked problem construct to businesses. Further, this study suggests that the problem faced by this firm remained difficult to tame precisely because it failed to employ a collective leadership approach. The contribution to the leadership literature comes from introducing Two-Eyed Seeing and showing how it may help produce leadership that is inherently more collective in nature. Beyond its instrumental value, this approach may nurture more consent-based relationships between businesses and Indigenous communities in Canada, as called for by the TRC, hence contributing to reconciliation with a long-suffering neighbouring Indigenous community.
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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 | 0.025 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.036 | 0.042 |
| Scholarly communication | 0.020 | 0.011 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".