Shady Figures and Shifting Grounds for Re/Truthing: Channeling McLuhan’s Posthuman
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
A dramatic shift in ground across the American political and social landscape is taking place, the kind that happens when a figure such as Trump conducts himself in the media, including by Twitter. In describing approaches to navigating a changing world through media, Marshall McLuhan employed the concept of figure/ground to evaluate media and their effects: a pursuit in honing perceptions. In curriculum theory, we employ figure/ground analysis to better recognize when a traditionally accepted humanist lens as figure has largely precluded recognition of a posthuman grounding that now thoroughly structures the conditions of the developed world’s existence (Sharon, 2014). How do we as educators address McLuhan’s prescient concerns over networked technologies and shifting media brought about by the electric age and now deployed by the likes of Trump, his administration, network news, and a disenfranchised American populace?
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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