NEXT-LEVEL LEADERSHIP : RAILROADS THAT EMBRACE CHANGE AND NURTURE INNOVATION ARE MORE LIKELY TO DEVELOP IT, STUDY SAYS
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
Upper management departures and shifts in Class I railroads highlight the industry's increased awareness of and need for aggressive recruiting and nurturing of top talent. The departures of Canadian National President and CEO Paul Tellier for Bombardier and CSX Corp.'s John Snow leaving to become President Bush's Treasury Secretary were two notable recent developments. Class Is are stepping up their management-trainee programs that give upper level employees cross- functional experience. They are also identifying employees with high potential for upper management positions and linking them to mentors. Both CN and CSX have programs to address these concerns. Among the other approaches is bringing in executives from other industries, as CN did when they hired a human resources executive from H.J. Heinz, a consumer products company. Developing a higher brand-awareness of the industry as a whole, improving compensation packages and company perks, and developing a more strategic succession process are among the approaches described.
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.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it