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Record W6888139466 · doi:10.18712/nsd-nsd0069-v2

Attitudes towards Norwegian Development Assistance, 1974

2022· dataset· en· W6888139466 on OpenAlexaboutno aff

Bibliographic record

VenueNSD – Norsk senter for forskningsdata · 2022
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNorwegianPublic opinionMeaning (existential)Period (music)Developed countryQuarter (Canadian coin)Peer reviewOfficial statistics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.214
Threshold uncertainty score0.425

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0190.004

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.

Opus teacher head0.040
GPT teacher head0.311
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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