Sensory Regimes in TV Marketing:Boardwalk Empire’s Chromatic Enhancement and Digital Aesthetics
Bibliographic record
Abstract
Providing a contribution to the growing research on the aesthetics of televisual promotion, this paper offers an empirical investigation of the multisensory appeal of HBO’s marketing of Boardwalk Empire, taking it as an example of a hyperaesthetics strategy of audience capture. To this end, the paper looks at the trailers for the show’s first season, as well as to its titles sequence and character posters, arguing that their chromatic enhancement, obtained in colour grading, invites a sensorial response, also contributing to confer a distinctive identity to its channel. In this light, hyperaesthetics is taken to stand for both an innovative approach to digital design, as maintained by Peter Lunenfeld, and as a marketing strategy of sensorial mobilisation, as theorised by David Howes. A look at HBO’s partnership with Canadian Club Whisky demonstrates the multisensory appeal of Boardwalk Empire’s campaign and its goal to brand the show as a lifestyle event. Even before we consume the actual show, this promotional strategy aims at embedding us within a semiotic and affective chain that prompts a variety of effects. The sensation of unqualified expectation and even excitement that is thus generated points toward marketing’s anticipative logic whereby hyperaesthetics generates affective attachment to as-yet unaired productions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".