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Record W4200213179 · doi:10.1177/10564926211063777

Assimilation, Integration or Inclusion? A Dialectical Perspective on the Organizational Socialization of Migrants

2021· article· en· W4200213179 on OpenAlexaff
Vedran Omanović, Ann Langley

Bibliographic record

VenueJournal of Management Inquiry · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsHEC Montréal
FundersForskningsrådet om Hälsa, Arbetsliv och VälfärdVetenskapsrådet
KeywordsDialecticSocializationSociologyContradictionWorkforceDisadvantageSituatedPerspective (graphical)Political scienceEconomic growthSocial scienceEconomicsEpistemology

Abstract

fetched live from OpenAlex

Given the increasing importance of migrations around the world, and the challenges that migrants face in entering the labor market, the process of socialization of migrants into organizations deserves more attention from management scholars. Indeed, societal discourses promoting equality and diversity often appear to be in contradiction with the unequal power relations migrants experience on entering the workforce. Drawing on a dialectic perspective and a qualitative meta-synthesis methodology, we show how the practices engaged in by organizations to socialize migrant employees are deeply embedded in and influenced by macro-social contexts that may place migrants at a disadvantage, giving rise to emerging tensions. We examine a range of contingencies that can mitigate the inequalities that migrants experience, and we reveal a variety of dynamic dialectical pathways surrounding migrant socialization practices through which they may be reproduced or transformed depending on the mutual relationships between situated conditions, emerging tensions and human praxes.

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)0.015
metaresearch head score (Gemma)0.009
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 score0.015
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0080.037
Scholarly communication0.0110.013
Open science0.0010.011
Research integrity0.0020.003
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 head0.154
GPT teacher head0.370
Teacher spread0.216 · 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

Citations48
Published2021
Admission routes1
Has abstractyes

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