Bibliographic record
Abstract
Many people want their heroes to be straightforward and simple figures. Reduced to almost cardboard cutouts, they become as much mythic caricatures as real-life characters; there is little room for nuance or contradiction in the composition. However, heroes are often ordinary people who are placed or find themselves in extraordinary circumstances. Behind the myth, there is a flesh-and-blood individual who is as or even more complex than most others. Indeed, some heroes build their claim to greatness around their experience as and empathy with the lives of ordinary people (like Lord Atkin, Chapter 5). The hallmark of their heroic status is to be found in the fact that they rise above but never forget their own ordinary existence; they scale the ladder of success, not to escape their ordinary lives, but with the avowed ambition of taking other ordinary people along with them on the climb. As resilient as he was resourceful, Thurgood Marshall was one such judge. He put his ordinary experience to extraordinary effect; he negotiated that perilous territory between celebrity and greatness. As talented as he was, he never forgot who he was, because, as an African American, he was never allowed to forget. Nor did he want to forget – “There are only two things I have to do – stay black and die.” No matter what he achieved or how high he rose, he would always be seen, for both better and worse, as a black man. The impact of his status and identity cannot be overestimated in reaching any assessments of his judicial legacy. He was a great judge (as well as a great citizen-statesman) both because and in spite of being an African American, with all that this implied in twentieth-century United States. Few judges can lay claim to having become such a public and revered personality.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.206 | 0.061 |
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".