Bibliographic record
Abstract
This paper describes how the evolution of winter maintenance has not been limited to equipment and materials. Shift schedule management can play a significant role in the economics of an operation. Standard practice for winter maintenance was to schedule three, hour shifts per twenty-four hour period in order to cover any snow and ice emergencies. This practice was subjected to extensive criticism for the periods between storm events. The first change reduced the three shifts to two balanced shifts per twenty four hour period with two four-hour periods being covered by placing staff on-call with a minimum time charge and additional overtime premiums, when applicable. Such arrangement eventually lead to the criticisms of overtime payment and the cost of supporting full crews on standby. The standby and on call conditions were that being placed on call caused a minimum three hour payment and where an actual call out occurred, that minimum was paid on top of an overtime premium for all hours worked. The current arrangement of shift hours and time management is for a specialized operation such as winter maintenance. The objective of this paper is to document the experiences of the Region of Ottawa-Careleton in achieving maximum benefits of shift labor management while working within the collective agreement.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".