Episode 107: Lethbridge Dodgers Manager Gail Henley
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
September is a big month on our calendar for \\"On This Date\\" events. As the summer winds down, regular seasons come to an end, leaving behind playoffs and championship runs. We have highlighted a number of those on social media, but wanted to bring one of the stories to life for the podcast. The Lethbridge Dodgers were a powerhouse in the late-70's and early-80's, capturing Pioneer League titles in 1977, 1979 and 1980. It's no small feat when you consider the high turnover of players the rookie leagues see. The one common denominator during those three seasons in Lethbridge was manager Gail Henley. The Los Angeles Dodgers' director of minor league development led Lethbridge to a 173-105 record in his four seasons (1977, 1979, 1980 and 1983). We chatted with Henley, who is approaching 92 years of age, about his memories of the province and what he's most proud of when he looks back on his life in baseball.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.860 | 0.151 |
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