The empowering potential of social media for key stakeholders in the repatriation process
Bibliographic record
Abstract
Purpose – The purpose of this conceptual paper is twofold. The first objective is to introduce a multi-stakeholder power perspective to the discourse on repatriate retention, which has, to date, treated issues of career agency without considering whether other stakeholders might be capable of responding constructively. The second objective of the paper is more prescriptive, conjecturing that social media, which has also been completely overlooked by the repatriation literature, has the potential to empower repatriation stakeholders. Design/methodology/approach – Following a review of the literature on repatriate turnover, this paper uses Hardy and Leiba-O’Sullivan's (1998) framework on empowerment to examine the nature and significance of powerlessness on the part of key stakeholders in the repatriation process – repatriates, HQ managers, and HQ HR professionals. It uses the same framework to investigate how social media might help to empower these stakeholders. Findings – The analysis finds that social media has the potential to empower repatriation stakeholders in four key ways: first, by triggering expatriates’ awareness of the need to proactively manage different aspects of their own impending repatriation; second, by providing access to supportive mentoring resources; third, by strengthening access to key HR and managerial decision-making arenas; and fourth, by enabling HQ managers and HR representatives to more judiciously direct potentially scarce organizational resources (including their own time) toward key repatriation supports. Research limitations/implications – Although this conceptual paper has no empirical data, it offers considerable value to the repatriation literature by introducing the topics of power and social media and explaining their relevance to repatriation (and indeed, to the field of international HRM). Practical implications – Repatriate turnover is problematic, both for repatriates who would have liked to remain with the organization that sent them on assignment, and for the organizations that would like to have retained (and utilized) repatriates’ global competencies. Thus, the main practical implication of this paper is that it offers an innovative contemporary solution (e.g. the use of social media) to this problem of repatriate turnover. Originality/value – The paper demonstrates that the topic of power has been completely neglected by the repatriation literature. Similarly, the topic of social media, has also been completely overlooked by the repatriation literature. This paper introduces these two topics to the repatriation literature, and, in so doing, broadens the understanding of constraints on repatriate agency as a means of repatriate retention, and offers innovative contemporary solutions (e.g. social media).
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".