Bibliographic record
Abstract
What human values would you deny to save your life? In this work of philosophical short story fiction, a group of families are on vacation touring Frank Lloyd Wright’s Fallingwater when they hear gunshots. While most are confused, one attuned man realizes the danger and quickly gets the children safely into the basement. The remaining group is then confronted by men with guns looking to sort out, and kill, everyone who are not Christian. They are, they say, trying to bring America back to its true values and roots. An offended black man confronts them, but they assure him, they aren’t racists, they are good Christian men. They kill a Jewish man, who makes clear while he believes Jesus was a good man, but not the son of God. The narrator’s husband is then picked next and asked to confirm his Christian faith. His wife knows he’s an atheist and tries to will him to lie. Instead, her husband confesses both his Canadian citizenship and his lack of Christian faith, and is killed. Shortly thereafter police snipers show up and show the gunmen dead. The families are safe, but the narrator must now explain to their two children in the basement, that their father is dead.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 0.009 |
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".