Working Remotely, Feeling Remote? The Role of Digitally Mediated Communication in Shaping the Identity of Virtual Expatriates
Bibliographic record
Abstract
Utilizing the social identity theory, this conceptual article has proposed how digitally mediated communication between expatriates and host country nationals (HCNs) in a remote work arrangement is linked with individualized change experiences of virtual expatriates. The conceptualized model proposes that the lack of in-depth conversations via virtual communication platforms leads to the development of weak emotional interactions between virtual expatriates and HCNs. However, weakened emotional interactions might result in positive or negative impact on expatriates' identity based on personality-based differences. In this regard, expatriates with collective self-esteem are likely to experience social identity threats because of weakened social ties with HCNs. Contrary to the above group, expatriates having personal self-esteem would view weak socialization as an opportunity and experience an improvement in their leader identity, thus experience a positive social identity change over time. This research has conceptually explored outcomes of digitally mediated communication between expatriates and HCNs on the identity change experiences of expatriates, and holistically covers the role of positive as well as negative change experiences. Unlike the focus of the majority of literature on traditional expatriation, the proposed model has focused on experiences of virtual expatriates, and how working in remote work settings lead to long-term socio-psychological changes in these individuals.
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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 | 0.002 | 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 | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".