Elizabeth Gaetjens Interview, 6 June 2013
Bibliographic record
Abstract
Betty Gaetjens is resident of Judson Place who has recently celebrated her 100th birthday. She has lived in Cleveland for her entire life, and graduated from Flora Stone Mather College in 1935. She talks about where she grew up and where she went to school. She also remembers going on various trips with her parents and later her husband and two sons. She tells about how she and her husband took their kids to all 50 states and 6 Canadian provinces before they were out of high school. A majority of what Mrs. Gaetjens said revolved around her involvement with the Great Books Organization. A group that got together and read books from the top 100 books, which has its origins in the University of Chicago. When it came to Cleveland, Mrs. Gaetjens joined the organization and eventually she became the leader her group. Often she used her experiences with the Great Books group to discuss her ideas on the importance of education, especially with finding oneself.Betty Gaetjens is resident of Judson Place who has recently celebrated her 100th birthday. She has lived in Cleveland for her entire life, and graduated from Flora Stone Mather College in 1935. She talks about where she grew up and where she went to school. She also remembers going on various trips with her parents and later her husband and two sons. She tells about how she and her husband took their kids to all 50 states and 6 Canadian provinces before they were out of high school. A majority of what Mrs. Gaetjens said revolved around her involvement with the Great Books Organization. A group that got together and read books from the top 100 books, which has its origins in the University of Chicago. When it came to Cleveland, Mrs. Gaetjens joined the organization and eventually she became the leader her group. Often she used her experiences with the Great Books group to discuss her ideas on the importance of education, especially with finding oneself.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.067 | 0.012 |
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".