MétaCan
Menu
Back to cohort
Record W6936947529 · doi:10.5878/000046

Class structure in Sweden 1980

2013· dataset· en· W6936947529 on OpenAlexaboutno aff

Bibliographic record

VenueSwedish National Data Service · 2013
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSocial classClass (philosophy)PoliticsSpouseGovernment (linguistics)UnemploymentPolitical structureSurvey data collectionWorking class

Abstract

fetched live from OpenAlex

The purpose of the survey is to describe and measure the Swedish class structure regarding mobility, political activity, attitudes and consciousness. A battery of questions addressed work-related issues such as supervision, decision-making, autonomy, respondents formal position in the hierarchy, ownership, credentials, and income. Other work-related data describe the size, industrial sector, and government or corporate linkage of the individuals employer. Further information was gathered on the class origins of the respondents family and of the families of the respondents spouse and friends. Data on class-related experiences such as unemployment and union participation were also collected, as well as data on the division of power and labour in the household. In addition the survey contained a broad range of questions on social and political attitudes and the respondents political participation. The study is part of the multinational study ´Class Structure and Class Consciousness´ (ICPSR 8413), which includes almost identificial studies from United States, Norway, Canada, and Finland.

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: Dataset
Teacher disagreement score0.060
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.007
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.011

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 head0.066
GPT teacher head0.332
Teacher spread0.266 · 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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueSwedish National Data ServiceFrench-language works237,207