Executive competencies and individual ambidexterity: shaping late-career transition to Canada’s recreational cannabis industry
Bibliographic record
Abstract
Purpose The authors contribute to scholarship on motivation for late-career transition, by examining how older executives drew on individual ambidexterity (IA) in the stigmatized, Canadian-licensed recreational cannabis industry. Design/methodology/approach The methodology utilizes a qualitative method, utilizing semi-structured interviews with 15 late-career executives. Inductive examination of data uncovered subthemes related to motivations for late-career transition, exploring and exploiting competencies, and known and unknown boundary conditions. Findings Motivations explained the impetus to join, while ambidexterity allowed executives to employ explorative and exploitive competencies to weather boundary conditions. Late-career transitioning to a stigmatized emerging industry presents an unprecedented mode of bridging employment for older workers. Research limitations/implications This small exploratory study of a nascent industry is limited in its generalization across different contexts but relevant to others in cannabis and other emerging industries. Increased focus on Human resources management (HRM) related research on late-career transition due to limited studies and IA. Practical implications Cannabis can be a risky employment venture for older workers that may affect future job prospects due to stigmatized views or present devastating financial risk. Older workers with knowledge, experience and skill remain relevant utilizing IA and their ability to manage difficult boundary conditions. Older experienced workers can bridge novel new opportunities before retiring. Originality/value The authors incorporated IA, expanding on literature related to boundary conditions in the late-career transition of executives into stigmatized recreational Cannabis. The authors introduce a new mode of bridge employment for late-career workers.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".