Bibliographic record
Abstract
The process of strategic planning is necessary to every court in order to define a consistent path to guide management on a daily basis. Although succession planning is a critical step to effective strategic planning, it is labor intensive and somewhat costly to achieve. The State Justice Institute (SJI) is gratefully acknowledged for their contribution of grant dollars that helped to fund the succession planning process for the 20 th Judicial Circuit and Ottawa County Probate Courts. This project required not only fiscal support but also, the endless support of the Courts’ judges. Without their support and faith, this project could not have achieved the transparent outcomes reflected in this report. Also, implementation of the project would not be possible without their support and belief in the value of planning for the future of the Courts. The Ottawa County Human Resource Department and the Ottawa County Administrator’s Office are also recognized for their support and willingness to share data. Such collaborative spirit supported the endeavor by providing valid, archived, unbiased data to enrich the workforce analysis. The Courts ’ administrative teams- Leadership and Supervisors- are extended sincere appreciation for their willingness to provide data, participate in data collection, offer feedback, pretest instruments and generally, support the endeavor through countless articulations of this project to staff. Their relentless assistance in all aspects of this process was truly appreciated. The Court staff are recognized for their patience and willingness to keep an open mind. It is hoped the staff will increasingly see the value to the Courts ’ future and to all those who remain employed by the Courts. B.B.S: ANALYZING THE COURTS ’ WORKFORCE 3
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 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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.350 | 0.195 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".