Bibliographic record
Abstract
This chapter outlines the theoretical contributions this book makes to Role Theory, while also offering the analytical framework employed to compare empirical cases of marginalised diaspora mobilisation in role contestation. It begins by discussing Role Theory and canvassing its recent applications as well as the parallel literature on diaspora influence on foreign policy. From an agency standpoint, I theoretically disaggregate domestic actors in role contestation by reconsidering “masses” in foreign affairs as distinct agents in “vertical role” contestation, through distinguishing between diaspora elites and foreign policy decision-makers and, finally, discussing how these agents interact. The second section of this chapter takes an institutional perspective to argue that domestic sources of role contestation are interested both in role conception as well as role performance, and this is especially true for diaspora agents. To ascertain whether diasporas have influenced role performance, I argue that international role constraints must be defined and, to do so, it is necessary for Role Theory to ascribe role position through state capabilities. Finally, I advance that states playing an “indispensable” role in subordinate international institutions are limited in their role performance options, and by extension their responsiveness to domestic interests, as potentially disruptive behaviour on their part could lead to the institutional dissolution.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.030 | 0.016 |
| Scholarly communication | 0.018 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".