Deciphering ‘Sons of the Soil’ Conflicts: A Critical Survey of the Literature
Bibliographic record
Abstract
Migration has always been a long-standing feature of political life throughout the world. In some cases, however, the arrival of large numbers of migrants has produced violent clashes between ethnically distinct ‘native’ or ‘local’ populations and migrants. These conflicts are commonly referred to as ‘Sons of the Soil’ (SoS) conflicts. Notwithstanding the growing interest in this form of conflict, a number of questions remain: What are the main features and dynamics of SoS conflicts? How do SoS conflicts differ from other types of conflicts (e.g. ethnic conflict, civil war)? What are the mechanisms linking migration to conflict, and how might these vary across space and time? By examining a wide range of methodological research on SoS conflicts in a plurality of regions (e.g. Africa, China, Europe, India, Russia, Southeast Asia), the article provides a comprehensive analysis on SoS conflicts and generates new conceptual and theoretical perspectives for deciphering the complex dynamics surrounding these conflicts.
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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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.017 | 0.020 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.010 | 0.019 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| 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".