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Record W2739046893 · doi:10.1108/edi-11-2016-0083

Recent immigrant newcomers’ socialization in the workplace

2017· article· en· W2739046893 on OpenAlexaff
Amina Malik, Laxmikant Manroop

Bibliographic record

VenueEquality Diversity and Inclusion An International Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsTrent University
Fundersnot available
KeywordsSocializationProcess (computing)Extant taxonSociologyImmigrationPublic relationsPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Purpose Despite the increase of recent immigrant newcomers (RINs) into the workforce over the past few years, many employers still face the challenge of successfully integrating RINs into the workplace. To this end, the purpose of this paper is to propose customized socialization tactics for RINs and highlight the role of RINs’ adjustment strategies in order to facilitate their workplace adjustment. Design/methodology/approach Drawing on immigrants, socialization, and diversity literatures, the paper develops a conceptual model of the socialization process for RINs and advances propositions to be empirically tested. Findings The paper proposes that customized socialization tactics by organizations and adjustment strategies by RINs would facilitate RINs’ socialization process by increasing their social integration and role performance, the factors which would ultimately help in their workplace adjustment. Research limitations/implications The proposed customized socialization tactics add to the extant socialization literature by highlighting the crucial role firms can play in RINs’ socialization process. Additionally, the paper highlights an important role of RINs in their own socialization process. Practical implications Organizations need to employ new, different socialization tactics to help integrate RINs in the workplace. RINs may find the research outcomes useful in acknowledging their own role for successful workplace integration. Originality/value This paper presents a new way of looking at organizational socialization tactics for RINs while highlighting a role of RINs themselves, and concludes by discussing theoretical, practical, and societal implications for organizations employing RINs.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0300.000
Scholarly communication0.0010.002
Open science0.0020.007
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.179
GPT teacher head0.383
Teacher spread0.204 · 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 teacher head, not a consensus.

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

Citations41
Published2017
Admission routes1
Has abstractyes

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