MétaCan
Menu
Back to cohort
Record W2987411992

SVERIGE OCH KANADA I FÖRÄNDRING? En kvalitativ analys av politisk diskurs fokuserad på Mångkulturalism och Civic integration

2018· article· sv· W2987411992 on OpenAlexaboutno aff
Susanna Karlsson

Bibliographic record

VenueKTH Publication Database DiVA (KTH Royal Institute of Technology) · 2018
Typearticle
Languagesv
FieldSocial Sciences
TopicSocial and Educational Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science
DOInot available

Abstract

fetched live from OpenAlex

"Sweden and Canada in transformation? - A qualitative analysis about governmental rhetoric focused on multiculturalism and civic integration.) Integration stole the spotlight and became the focus of political discussions after some intense years of increased immigration. Rising fears about failed socio-economic and socio-political integration caused many states to make changes in their integration policy's. However, the content varies considerably between countries and do not always reflect the state of the political discourse. Therefore, this study analyses political statements using ideal types to find out whether two specific integration concepts, multiculturalism and civic integration, that has gotten much attention in both academic and political circles, can be found to have changed in Sweden's and Canada's political discourse. It seeks to describe specifically if the political discourse on the highest level focused on civic integration and multiculturalism, has changed due to increased immigration and in face of new challenges between 2011-2017. The result implies that Canada's political discourse 2011 reflected multiculturalism and then fluctuated between the years investigated but turned back to being more coloured by multiculturalism. The same fluctuating pattern is found in results for Sweden's political discourse, but the country's discourse stronger reflected civic integration both 2011 and 2017.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.006
Science and technology studies0.0020.005
Scholarly communication0.0000.003
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.035
GPT teacher head0.343
Teacher spread0.309 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueKTH Publication Database DiVA (KTH Royal Institute of Technology)Same topicSocial and Educational SciencesFrench-language works237,207