<i>Governing the displaced: Race and ambivalence in global capitalism</i> Dr Ali Bhagat
Bibliographic record
Abstract
Governing the Displaced examines themes of fantasy, disposability, and survival that manifest themselves in transnational refugee governance. Through dual case studies in Paris and Nairobi, Bhagat shifts scholarly focus away from the refugee camp and towards cities to reveal the multiple spaces in which the everyday struggle for refugee survival occurs. He situates two seemingly disparate cities within a multiscalar analysis to illuminate how refugee survival cannot be separated from the national and transnational contexts in which neoliberal approaches to refugee governance are embedded. Bhagat posits that the logic of neoliberal capitalism produces an ambivalence towards refugees, whereby states are caught between countervailing desires for labour and austerity. States recognize the economic potential of refugees as productive labour, although welfare retrenchment and inadequate social policies place refugees in a daily struggle for survival amidst urban unaffordability, inadequate social housing, labour insecurity, and widespread xenophobia. Through in-depth interviews with refugees, NGOs, and state officials between 2017 and 2018, Bhagat reveals the disciplinary nature of refugee governance policies and how these exclude refugees from shelter, work, and political belonging.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".