Brandscapes of control? Surveillance, marketing and the co-construction of subjectivity and space in neo-liberal capitalism
Bibliographic record
Abstract
This article considers the emergence of the ‘brandscape’ as a new apparatus and a mode of order in neo-liberal capitalism. Simultaneously locating its emergence as a result of developments in marketing, urbanism, technology and surveillance, we discuss its characteristics, forms and potentialities. The brandscape is a marketing neologism that combines the concept of the ‘brand’ with ‘landscape’. Based on the notion of the brand, which seeks to give reassurance and familiarity to customers by semiotic visual codings of product ranges, brandscapes in consumer spaces have an inherent experiential quality and form the basis of the new affective economy. The brandscape recodes the consumer subject as a spatialised, desiring, networked body produced through a complex of marketing techniques designed to analyse buying behaviour, target consumers, and seduce them with strongly affective experiences. Working as immaterial labourers, through the constant provision of consumer data upon which the brandscape rests, consumers become exploited as well as exhilarated. Brandscapes also become securityscapes, as their boundaries and interiors are heavily policed to protect the dreams of safety and riskless living they proffer. However, as simulated consumer subjects are reinscribed onto the material, we note both the tendency to failure in the assumptions of the underpinning marketing processes and the competition to brandscapes from other visions of security and ubiquitous computing futures. But the problems of brandscapes provide the context for a move from biopolitical to neuropolitical control, as the brain, rather than affect, becomes the new site of contestation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.071 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".