Sustained success through the management of core competencies: an empirical analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The authors examine the relationship between the management of core competencies and long-term success for functional quality teams. The analysis focuses on the following hypotheses: functional quality teams in high-technology companies that are organized around the management of core competencies are more successful in the long run than functional quality teams which are not; different functional quality teams have different core competencies: the portfolio of core competencies depends on the specific role played by the team; and the portfolio of core competencies of a functional quality team evolves with the changing role of the team. Even though the amount of data is too small to be able to show statistical significance, they do tend to show support for all three hypotheses. A result of special interest was the suggestion that, even though core competencies management seems to be associated with success, none of the core competencies management steps taken individually will bring success to the functional quality team. The four steps of core competencies management seem to have a synergistic effect that can result in better performance.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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 it