Bibliographic record
Abstract
The lead-up to and the aftermath of the 2016 referendum on the United Kingdom’s membership in the European Union have been characterized by particular psychic reactions and affective states: shock, perplexity, anxiety, guilt, paranoia, anger, depression, delusion, and manic elation. The debate over Brexit has played out largely in an affective register. Scholars and journalists in search of explanations have reached for psychological concepts such as amnesia and have cited feelings, specifically nostalgia and anger, as major factors. Paul Gilroy’s Postcolonial Melancholia provides a more useful analytical framework for constructing histories of Brexit beyond the usual narratives of reversal, unexpected rupture, or liberation, and for unearthing the psychic attachments and affective dynamics underlying such narratives. Gilroy’s conception of postimperial melancholia allows us to see the links between Brexit, anti-immigrant racism, and the obsession with national identity, and the unacknowledged and ongoing legacies of empire and decolonization in contemporary Britain.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".