©2013 Canadian Journal of Communication Corporation Reviews Authentic: The Politics of Ambivalence in a Brand Culture. By
Bibliographic record
Abstract
Authenticity: a word that is seemingly so overused that it provokes both pundits and supporters. Authenticity appears at odds with branding, yet as Sarah Banet-Weiser argues in her com-pelling book, Authentic: The Politics of Ambivalence in a Brand Culture, there are “authentic ” branded citizens, branded creativity, branded politics, branded religion, and even branded self-identity. The central focus of this book is how can we live an authentic life with and through brands. Authentic is a timely book that stands in opposition to, or as an appropriate critical backdrop to, understanding the hype sur-rounding self-branding, authenticity, and individuality. Banet-Weiser argues that by resisting the temptation of binary logic and embracing ambivalence we can understand the complex ways in which people live in a branded society. Ambivalence is the liminal space between these two sides where economic imperatives/inauthentic commerce and authenticity co-exist in a love-hate relation-ship. Banet-Weiser shatters the hackneyed belief that we live in an inauthentic world where people crave authentic experiences. The book is organized into five relatively discreet chapters that carve out a space
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.404 | 0.172 |
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".