What’s wrong with Muslims? screening conflict and identity within France and Britain’s suburbs
Bibliographic record
Abstract
The book presents a collection of readings to reflect and develop the varied and dynamic interfaces of globalization: the global and local. The purpose is to identify how global and local dimensions intersect with cultural construction and processes of identity. How do the images around us challenge us in everyday life? We are surrounded by a multitude of images in cultural contexts, with rich semiotic signs and symbols, manifest in posters, graffiti, advertising, the media, photographs, religious representation, sculpture, and myriad art forms. In the context of this assortment of representations, we explore visual sociological threads and constructs that emerge from issues evoked by modern ideas about globalization. This important contemporary theme is moved by the parameters of visual sociology, whereby photographic images in various contexts illustrate, reflect, and generate sociological concepts and theories. The collected writings point to a global stage, as we are guided through lands such as Australia, Britain, Canada, Egypt, France, Italy, and Lithuania, in the quest to understand globalization through prisms such as community, class, gender, ethnicity, and religious background. The book addresses the role of visual communication in an examination of these various theoretical facets, and explores ways in which individuals and institutions exchange information about themselves, their identities, their values, and their ideas of belongingness in the varied guises of culture.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.026 | 0.022 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".