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Record W7117970362 · doi:10.17605/osf.io/b7fsc

Cross-National Study of Norms of Assimilation and Immigration National Origin

2024· other· W7117970362 on OpenAlexaboutno aff
Morris Levy

Bibliographic record

VenueOpen Science Framework · 2024
Typeother
Language
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCultural assimilationImmigrationAssimilation (phonology)Country of originEmigrationCultural diversity

Abstract

fetched live from OpenAlex

This experiment aims to assess whether norms of assimilation - what native-born people believe that immigrants in their host country should do to assimilate - varies across immigration national origin groups. It asks specific questions about assimilationist expectations ranging from "functional" assimilation (things conducing to self-sufficiency) to adoption of core liberal values, to cultural customs such as food, dress, and celebrations, to the hardest types of assimilationist demands, which involve abandonment of immigrants' own private customs from their countries of origin. In addition to the experimental effects, an important observational component of the study involves assessing differences in patterns for support for assimilation across countries, with particular attention to the comprehensiveness of cultural demands of European publics versus US and Canadian (settler society) publics.

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)0.006
metaresearch head score (Gemma)0.013
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.060
GPT teacher head0.438
Teacher spread0.379 · 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
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
Published2024
Admission routes1
Has abstractyes

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