The protean approach to managing repatriation transitions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although top‐down interventions have the potential to reduce repatriate turnover, most organizations have not been very accommodating and repatriate turnover continues to remain high. Drawing from career transitions theory and the protean perspective of career management, this paper proposes a model of repatriate proactivity as an alternate approach. A “successful” repatriation transition outcome is defined as one in which, upon return, the repatriate: gains access to a job which recognizes any newly acquired international competencies; experiences minimal cross‐cultural re‐adjustment difficulties; and reports low turnover intentions. Individual antecedents are posited to include proactive repatriation behaviors and the personality characteristics which are suggested to drive the use of these behaviors. The strength/weakness of the repatriation situation is posited to moderate the relationship between personality and the emergence of proactive repatriation behaviors. Practical and theoretical implications for both the repatriation problem, and the career development literature in general, are discussed.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it