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Record W4294577823 · doi:10.1007/978-3-031-13231-5_6

The Macro Context of Immigration

2022· book-chapter· en· W4294577823 on OpenAlexaff
Luciara Nardon, Amrita Hari

Bibliographic record

VenueInternational Marketing and Management Research · 2022
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsCarleton University
Fundersnot available
KeywordsSensemakingNarrativeImmigrationContext (archaeology)MulticulturalismSociologySocial workPolitical sciencePublic relationsPedagogyGeography

Abstract

fetched live from OpenAlex

Abstract This chapter explores the role of the broader social context in QIs’ work integration and sensemaking of their career options and actions. Sensemaking is ongoing and occurs within a dynamic social environment. The institutional level of sensemaking exposes the relationship between the broader society and individual actions. We discuss narratives of multiculturalism and professional attainment as prevailing master narratives that inform QIs’ and local citizens’ sensemaking of immigration and the influence on immigrants’ work integration. We conclude with a reflection on the relationship between immigration and settler colonialism.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.009
Scholarly communication0.0060.002
Open science0.0000.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.001

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 head0.054
GPT teacher head0.363
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; 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
Published2022
Admission routes1
Has abstractyes

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