Bibliographic record
Abstract
This paper offers a critical evaluation of anti-trafficking campaigns spearheaded by some in the feminist movement in an attempt to deal with the issues of unsafe migrations and labour exploitation. I discuss how calls to “end trafficking, especially in women and children” are influenced by – and go on to legitimate – governmental practices to criminalize the self-willed migration of people moving without official permission. I discuss how the ideological frame of anti-trafficking works to reinforce restrictive immigration practices, shore up a nationalized consciousness of space and home, and criminalize those rendered illegal within national territories. Anti-trafficking campaigns also fail to take into account migrants’ limited agency in the migration process. I provide alternative routes to anti-trafficking campaigns by arguing for an analytical framework in which the related worldwide crises of displacement and migration are foregrounded. I argue that by centering the standpoint of undocumented migrants a more transformative politics emerges, one that demands that people be able to “stay” and to “move” in a self-determined manner.
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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.016 | 0.059 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.014 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".