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Record W2555083626 · doi:10.13140/rg.2.1.4816.2321

THE MANY FACES OF BRAZILIAN IMMIGRANTS IN ONTARIO

2009· article· en· W2555083626 on OpenAlexfundaboutno aff
Lílian Magalhães, Denise Gastaldo, Guilherme Martinelli, Adao Hentges, Tatiana P. Dowbor

Bibliographic record

VenueTSpace (University of Toronto) · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Identity, and Health
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsImmigrationGeography

Abstract

fetched live from OpenAlex

The first part of the report concentrates on a quantitative and qualitative description of the study respondents. The respondents are characterized according to: 1) sociodemographic data; 2) immigration and adaptation aspects; 3) family and social aspects; 4) labour aspects, and 5) social representations. The second part of the report covers points of analysis relating to all of the study respondents. In the third part, the respondents were sub-divided according to their migratory status in Canada. In that part these authors present: 1) a brief description of the group of immigrants living and working in Ontario without any legal status to do so, and 2) a more detailed description of the group of permanent residents and of Brazilians who already have Canadian citizenship. In conclusion, we present some final considerations and recommendations for programs, policies and future studies.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.018
GPT teacher head0.278
Teacher spread0.260 · 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 designQualitative
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

Citations4
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueTSpace (University of Toronto)Same topicMigration, Identity, and HealthFrench-language works237,207