Attitudes towards Norwegian Development Assistance, 1974
Bibliographic record
Abstract
Surveys on attitudes to U-help has been conducted by Statistics Norway in 1972, 1974, 1977, 1980, 1983, 1986 and 1990, commissioned by NORAD. The investigations have been carried out as additional studies to labor force surveys (LFS). The aim has been to survey attitudes of Norwegian development assistance and provide data for studying the factors that influence these attitudes. In 1974, one applied as in 1972 to identify people's knowledge of foreign aid. Later, emphasis is being placed on studying people's perceptions of media coverage of the developing countries and aid issues. Investigations are continuing after 1990 as part of SSBs omnibus, in March 1993, May 1995 and November 1996. Even before 1972, it was conducted surveys on attitudes to foreign aid. A list of questions asked by the Norwegian Gallup in the period 1953-1965 are in Bjørn Alstad (ed) "Norwegian Opinions", Oslo, 1969. For a review of other relevant studies, see Theo Koritzinsky: "Voters, parties and foreign policy analysis of Norwegian attitudes 1945 - 1970" (Oslo 1970). See also Leif Vetlesen: U-help and public opinion. Norkontakt No. 7-8 1974 For general surveys of public opinion in this area, see Kristen Ringdal "Opinions on development aid from 1953 to 1975", PRIO Oslo 1975, Kristen Ringdal "People Its meaning and the Third World", Oslo 1979. For access to the dataset, use NSD application form: http://www.nsd.uib.no/nsd/english/orderform.html
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".