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Record W4294577556 · doi:10.1007/978-3-031-13231-5_3

The Immigrant Sensemaker

2022· book-chapter· en· W4294577556 on OpenAlexaff
Luciara Nardon, Amrita Hari

Bibliographic record

VenueInternational Marketing and Management Research · 2022
Typebook-chapter
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsCarleton University
Fundersnot available
KeywordsSensemakingIdentity (music)NarrativeContext (archaeology)ImmigrationWork (physics)Process (computing)Power (physics)SociologyPsychologyPolitical sciencePublic relationsEngineeringComputer scienceGeographyAesthetics

Abstract

fetched live from OpenAlex

Abstract Sensemaking starts with the sensemaker; the process of identity work is thus central to immigrant integration. In this chapter, we discuss individual level sensemaking to understand how qualified immigrants (QIs) facing similar work integration challenges, with comparable education and work experiences, can have widely different career trajectories and outcomes. We integrate narratives from QIs to explore identity processes involved in sensemaking and argue that identity work is a social process that is continuously in flux; it is dependent on context and imbued with power discrepancies.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.021

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 studies0.0070.008
Scholarly communication0.0070.006
Open science0.0010.006
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.068
GPT teacher head0.390
Teacher spread0.322 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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