Bibliographic record
Abstract
Our man is the consular officer at the Permanent Mission of the Republic of Zimbabwe to the United Nations office in Geneva, which also serves as the country’s embassy to Switzerland. At fifty-five and in his first foreign posting, he is a latecomer to the Internet and all its glories. “Baba, get e-mail,” his children said back in Harare. There was no need, he always said. Too expensive, too set in his ways. In Geneva, the connection comes with his telephone line. Night after night finds him enmeshed in the World Wide Web, scrolling through e-mails spun in places he has never been, e-mails that are woven into his life and leave him blinking before his computer screen. He types slowly, with two fingers, his tongue between his teeth. “Like a policeman typing a report on a burglary,” his wife teases him, “at the Charge Office in Harare.” See how easy communicating becomes, says his daughter, Susan, in England. Don’t forget to send the installment for the next semester. She follows the sentence with several bouncing bald, yellow, bodiless cartoon heads that open their mouths in toothless smiles as they wink at him. Baba, I need money, is the echo from his son, Robert, in Canada. Improve your credit rating, says Frederick Turk.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".