Bibliographic record
Abstract
Leadership and management practices are key factors inthe sustainability of rapid growth and high performance in small- tomedium-size businesses (SMEs).Most SMEs are unable to sustain suchgrowth.This article identifies five management practices that can aidSMEs in adapting to this growth.In order to identify these practices,interviews were conducted with 15 CEOs from Canadian high-growthentrepreneurial ventures, and literature discussing complexity sciences andself-organizing behavior was reviewed. These practices provide the necessary infrastructure for SMEs when theformal structures and systems already established are unable to support therapidly growing company.The five practices, which are part of the largerbehavior of self-organizing, are business logic, capture and share information,build relationships, manage organizational politics, and leadership style. Establishing a clear vision and being available for the employees--coreconcepts of business logic--allows CEOs to steer the direction of the companywhile still encouraging employees to be creative and share new ideas.W.L.Gore & Associates is one example of a company that has been able to usesuch practices to maintain fast growth and high performance for almost 50years. (SRD)
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 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".