Political Detentions, Political Deportations: Repressive Immigration Enforcement in Times of Trump
Bibliographic record
Abstract
During the presidency of Donald Trump, US Immigration and Customs Enforcement (ICE) targeted migrant justice activists, journalists, and advocates with deportation proceedings. The recent political repression has a revanchist character that appears to be a new pattern introduced by Trump but is part of a longer project of securing the smooth functioning of economic and racial social control in the US. I read the recent political repression of activists in relation to texts produced by radical intellectuals who endured political repression in two prior historical moments: the detention and deportation of radicals in the McCarthy era through the words of C.L.R. James; the policing and imprisonment of Black radicals in the early 1970s through the words of Angela Davis. In a third moment, I situate the recent pattern of Trump-era political repression in a context of ongoing contestation over interior immigration enforcement. The struggle over immigration enforcement is not only about legality, but also about the politics of race and class marginalization in the US.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.028 | 0.042 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.014 |
| Insufficient payload (model declined to judge) | 0.002 | 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".