Out-of-home advertising media: theoretical and industry perspectives
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Out-of-home (OOH) advertising media traditionally have not accounted for a large share of advertising budgets, but overall expenditure has grown considerably in recent years. Due to the transformation of the OOH advertising media landscape, and the diversity and ubiquitous nature of these media, there seem to be a discrepancy between the views of academic and industry experts on exactly what constitutes contemporary OOH advertising media. This article addresses the identified academic-practitioner divide by presenting both sides of the coin. An integrative review of OOH advertising media taxonomies in prominent academic sources, as well as specialists’ industry publications from Canada, South Africa, America, Australia, Ireland and the United Kingdom, was conducted. This resulted in a new conceptualisation of four key platforms for a contemporary OOH advertising media classification framework: outdoor advertising, transit media advertising, street-and-retail-furniture advertising, and digital and ambient OOH media. Clear direction for future research was given, specifically testing the proposed conceptualisation, the impact of OOH audience environments and mood on message delivery, and digital OOH advertising as one of the fastest growing media types.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it