Crying, “Wolf!” The Campaign Against Critical Race Theory in American Public Schools as an Expression of Contemporary White Grievance in an Era of Fake News
Bibliographic record
Abstract
The recent fervor over Critical Race Theory (CRT) in American public schools is the result of a confluence of contributing factors including: an eroded news media apparatus operating within a capitalist framework where an increasing portion of the American populace consume news through hyper-partisan cable news networks and social media that comports with their individual ideological preference; the decrying of CRT in schools as the latest iteration of historically-reliable White Backlash; and a highly-effective conservative messaging apparatus skilled in fomenting White Rage based on disinformation. In this essay I will, first, briefly survey America’s collapsing contemporary news media industry before discussing contextualizing White Rage throughout American history. From there, I will transition the article’s focus to the modern conservative media machine pushing fake news highlighting the (non-existent) issue of CRT in primarily suburban public schools as an exemplification of White Rage to protect whiteness and its hegemony for political gain.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.033 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.004 | 0.009 |
| 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".