Call Centre Karma, or How Popular Culture Learned to Stop Worrying and Love Outsourcing
Bibliographic record
Abstract
Since 2006, numerous movies and TV series have depicted outsourcing to India as a source of both economic and personal opportunity for American, Canadian, British and Indian characters. There has been no sustained assessment, however, of individual screen texts which address call centre work, nor any comparative work that might shed light on the significance of this transnational phenomenon. Using discourse and visual analysis, films including Outsourced, The Other End of the Line, The Best Exotic Marigold Hotel, and The Second Best Exotic Marigold Hotel, and TV series such as Outsourced and Mumbai Calling are shown to address popular fears over outsourcing by positing a shared neoliberal worldview, one that traverses national boundaries and histories, drawing both on enduring orientalist stereotypes and narrative tropes, as well as recent trends in Bollywood and American popular culture. These screen texts contain a limited critique of late capitalism, but nonetheless reimagine the purported risks of globalization as founts for potential benefit, both material and social, and often reconfirm the essential superiority of the West and Westerners.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.021 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".