Dean, Fred (audio interview #1 of 6)
Bibliographic record
Abstract
SUBJECT BIO - Fred Dean was a local businessman who prospered when the radios he sold became popular. He was also interested in local politics and appointed to the boards of directors of such public agencies as the Long Beach Water Commission and the Metropolitan Transit Authority (MTA). In this series of interviews, that were conducted as part of a project to study the impact of oil on Long Beach, Dean talks about his public service. He was on the MTA board when the Pacific Electric street cars stopped running in southern California and he served on the Water Commission when they sold some of their land for commercial development. Dean was also an active member of the Long Beach Mounted Police and as urban sprawl engulfed Long Beach, he fought to keep part of town where they could keep their horses. \n \nTOPICS - Fred S; Dean Day; Optimist Club; Eunice Sato; houses; stables; and Boy Scouts; Montana Land Company; Boy Scouts; and Will J; Reid Scout Park
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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads 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".