Affective Borderwork: Governance of Unwanted Migration to Europe Through Emotions
Bibliographic record
Abstract
This article explores how contemporary European migration governance utilizes affect and emotions to govern (unwanted) migration. Building on ethnographic fieldwork, we aim to show how emotions are used to bring the border alive beyond the actual geographical border, both inside Europe and in countries of origin. By juxtaposing two cases we highlight the interlinkages but also the differences between an, IOM-led, information campaign targeting the emotional register of the local population in rural Senegal, and a series of motivational interviews conducted by the Danish police targeting rejected asylum seekers refusing to return to their country-of-origin. We demonstrate how particular emotions are harnessed in these interventions to evoke morally charged spatial geographies that normalize racialized global inequalities to impact the (im)mobility of unwanted migrant subjects. Additionally, we seek to disentangle the ambivalent encounters between the interventions and the people they target. We analytically bridge cases that are often dealt with as separate phenomena in the academic literature, to tell a more nuanced story of how contemporary affective borderwork shapes European border externalization and internalization practices.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".