Applying the ABC s: Dressed & Ready
Bibliographic record
Abstract
This chapter discusses the set of behavior and results expectations called Dressed & Ready that was implemented in Canadian National Railways (CN). Supervisors were to prepare assignments before they left work the previous day, posting them so that, when employees walked in for their next shift, they saw immediately what equipment they would need. This change meant that employees were able to go to their lockers only once and get everything they needed for the work day. Like all bad habits, the old ingrained behavior was difficult to alter. As an organization, there were decades of comfortable old routines in place that both employees and managers did not want to let go. However, positive consequences began to gain momentum. More and more teams started showing up 100% Dressed & Ready. An unexpected plus emerged from spiking the switch on Dressed & Ready. Some employees had always arrived on time and put in their full day of work, despite what those around them did. Now they were becoming recognized as leaders and early adopters. When people are rewarded positively, their behavior gets reinforced.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.081 | 0.026 |
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".