International Departures: Radical Relational Lessons from Cross-Border Migration Corridors for Peace
Bibliographic record
Abstract
The rise of borders’ securitization has had established effects on the societal, security, and economic relations between states worldwide. In this paper, though, we argue that the usual level of analysis regarding border spaces is insufficient, as a state-based or neo-liberal approach ignores important realities and stakeholders that must be considered in these regions’ peacebuilding and governance. Using the illustrative cases of flagship species – pollinators (Monarch butterflies, hummingbirds) at the US/Mexico border and Megafauna (wolves, bears, reindeer) at the Finnish/Russian border, we show that non-human migratory corridors must be included as part of a more complex and radical relational understanding of securitized borders. Traditional use by humans in these spaces similarly needs to be incorporated into any sustainable governance approaches. Critical, decolonial, and feminist peace and conflict studies, as well as radical relational approaches, invite us to include local and Indigenous voices in bordering policies, to fight epistemological violence, inequalities, and discrimination, and to better address the challenges that borders entail, especially within the context of climate change. Radical relational understandings (including human relations with non-human migratory actors) offer a holistic understanding of these issues, especially as climate change increases pressure on human and non-human cross-border migration around the world.
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How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".