Politics of Fear versus Global Anxiety: A Critical Analysis of Recent US Anti-Immigration Policies from Psychoanalytic Perspectives
Bibliographic record
Abstract
Applying selected psychoanalytic constructs from Freud and Klein to recent pervasive rhetoric around anti-immigration in the United States, we conducted a critical discourse analysis of media and policy representations of immigrants in recent news coverage in the United States regarding the Trump Administration’s response to (1) asylum claims related to domestic violence and gang violence and (2) undocumented immigrants. We illustrate how feared bad object/immigrants are constructed alongside the imagined good object/nationalism, as exemplified by Trump’s motto – “Make America Great Again” (MAGA). We argue how this paranoid-schizoid position reifies racism veiled under nationalism and discuss how social workers could work together toward the depressive position re-imagining America-as-the-whole.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.021 | 0.062 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.009 |
| 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".