Bibliographic record
Abstract
The single greatest cause of corporate underperformance is the failure to execute. Author Ram Charan, drawing on a quarter century of observing organizational behavior, perceives that such failures of execution share a family resemblance: a misfire in the personal interactions that are supposed to produce results. Faulty interactions rarely occur in isolation, Charan says. Far more often, they're typical of the way large and small decisions are made or not made throughout the organization. The inability to take decisive action is rooted in a company's culture. But, Charan notes, leaders create a culture of indecisiveness, and leaders can break it. Breaking it requires them to take three actions. First, they must engender intellectual honesty in the connections between people. Second, they must see to it that the organization's "social operating mechanisms"--the meetings, reviews, and other situations through which people in the corporation do business--have honest dialogue at their cores. And third, leaders must ensure that feedback and follow-through are used to reward high achievers, coach those who are struggling, and discourage those whose behaviors are blocking the organization's progress. By taking these three approaches and using every encounter as an opportunity to model open and honest dialogue, a leader can set the tone for an organization, moving it from paralysis to action.
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.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.021 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".