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Record W4230882936 · doi:10.32920/ryerson.14663412

The impact of intercultural communication competence on the career experiences of skilled immigrant managers in the greater Toronto area

2021· preprint· en· W4230882936 on OpenAlexaffabout
Suhair Deeb

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsIntercultural competenceImmigrationCompetence (human resources)Human capitalEmpirical researchPhenomenonSociologyIntercultural communicationPsychologyPedagogySocial psychologyPolitical scienceEconomic growthEconomics

Abstract

fetched live from OpenAlex

"Guided by James Frideres’ model of integration and Pierre Bourdieu’s theoretical approach to capital, this paper examines the factors that contributed to the upward mobility of some skilled immigrants in the Greater Toronto Area. An examination of the literature on the phenomenon of the “glass ceiling” reveals that skilled immigrants’ integration into the workplace is multidimensional, and cannot be achieved without the accumulation of different forms of capital necessary for advancement. The empirical research of this study captured the participants’ professional experiences that led them to develop an intercultural communication competence, which became a fundamental component to their career development. Based on this finding, I offer a new conceptual model of integration into the workplace that can be achieved through the accumulation of intercultural communication and identity forms of capital. The paper advances recommendations for an in-depth investigation of the impact of formal and informal training, in the host country, on skilled immigrants’ upward mobility. Keywords: Intercultural communication, career advancement, skilled immigrants, forms of capital, Greater Toronto area."

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score0.651

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.003
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.046
GPT teacher head0.319
Teacher spread0.273 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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