Bibliographic record
Abstract
The interview was recorded at the Stockholm, Sweden, on November 7, 1990. The Interviewer was Jean Krasno. Per Lind was assigned to the Council of Europe affairs in the Sweden's Foreign Ministry in 1951, where he worked under and got to know Dag Hammarskold. When Hammarskold was elected to be Secretary‑General of the United Nations in 1953, he asked Mr. Lind to come with him to New York as his personal assistant. Mr. Lind served as the Secretary-General's personal assistant for the first three years of his term, returning to Sweden to rejoin the Foreign Ministry at the end of 1955. He became the deputy director of the Political Department at the Foreign Office from 1959-1963 and Deputy Undersecretary in 1962. In 1964, he entered diplomatic service, serving as the Ambassador to Ottawa from 1965 to 1969, to Canberra from 1975 to 1979 and to London from 1979 to 1982. Retired at the time this interview was conducted on 7 November 1990, Mr. Lind recalls his close relationship with Dag Hammarskjold before the Secretary-General's untimely death and the personal writings he left behind.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.228 | 0.157 |
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".