The hardware and software of Trumpism: A figure/ground analysis
Bibliographic record
Abstract
This article probes into Trumpism using McLuhan’s idea of figure/ground analysis. To make visible the hidden ground behind a salient figure (or figures), the dichotomy of instrumental and environmental approaches to media effects is introduced. The widely used instrumental approach is rooted in the long-standing Lasswellian tradition of communication studies (‘who says what, in which channel, to whom, with what effect?’). The instrumental explanations of Trumpism are unavoidably reductionist, as they focus on figures and, therefore, overemphasize rationality and agency in media use. On the contrary, the environmental approach focuses on hidden ground and explores what environmental forces originate from new media’s proliferation and how these forces reshape habitat and inhabitants. To apply this view, the article examines the environmental factors within the news industry and social media that are favourable to Trumpism: the commodification of Trump by the media, the morphological conflict between broadcasting and engaging modes of agenda-setting, the built-in polarization of social media and others.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".