Bibliographic record
Abstract
Amanda Bryant-Friedrich (Fig. 4.1) is Dean of the College of Graduate Studies at the University of Toledo (Toledo). Amanda was born in Enfield, NC, a small town about fifteen miles from the North Carolina-Virginia border. Her father was a farmer and her mother was a housewife. Her father only had a sixth-grade education and did not read or write much. Her mother graduated from high school in Enfield. Her maternal grandfather was a child of a slave and her mother was one of twenty-two children from two wives. They lived on a farm owned by a man named Whitaker. As her mother’s family had been enslaved by the family that owned the farm, her last name was Whitaker. Amanda’s paternal grandfather was a businessman who owned his own farm, on the other side of town. He was also involved in the illegal production of moonshine. Amanda went to Unburden Elementary School in Enfield. Her first experience with school was dramatic, because she lived at the end of a dirt road and was really isolated from other families. The first day she went to kindergarten she saw all those little kids, and she was afraid because there were too many people there. But the daughter of her mother’s best friend was there and invited her to come in to the classroom. Her first science class was in general science in fourth or fifth grade. She was so fascinated, she changed her mind about her future career of secretary or teacher and decided on science. Amanda went to Enfield Middle school in Halifax County, then the second poorest county in the state. The school had only basic infrastructure for science classes. She remembers her middle school chemistry teacher, Ms. Crowley, who told the students to put a mercury thermometer in a cork and Amanda accidently stuck it in her hand. They did not have much in the school, but her teacher taught her what she could.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.375 | 0.201 |
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".