Recent immigrant newcomers’ socialization in the workplace
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".