Modesty in Leadership: A Study of the Level Five Leader
Bibliographic record
Abstract
Human resource metrics and in particular, the management practices that impact bottom-line performance, have received increasing interest in recent years in the business community, as companies look to human capital rather than industrial capital to achieve success. A study that has garnered a great deal of attention in this area is the subject of Jim Collins' best-selling book Good to Great (2001). In it, Collins reports on the findings of his research team in their analysis of companies who significantly out-performed their competitors over an extended period of time. The research team examined companies who had a 15-year cumulative stock return at or below the general stock market and then cumulative returns that were at least three times the market over the next 15 years. The researchers further stipulated that the firms had to perform exceptionally regardless of the performance of their industry. Of 1,435 companies studied, only 11 met their criteria. Although Collins specifically tried to avoid having his team examine the leadership style of the CEOs, the researchers persuaded him that a common leadership style was shared by the leaders of all 11 companies and should not be ignored. This leadership style which Collins eventually termed the "Level Five leader" was characterized primarily by two things: modesty and an overwhelming sense of commitment to the organization above self. Collins admits in Good to Great that this finding did not fit the preconceptions of the research team.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 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".