Bibliographic record
Abstract
In this essay, I will argue that consumerism eclipses our collective ability to pursue and create a healthy public realm, and that education should function as a means of critiquing and resisting, rather than facilitating, this process.As schools turn increasingly to alternative revenue sources, corporate logos and brands populate hallways and classrooms, school buses and gymnasiums, textbooks and yearbooks.I will draw on Jean Baudrillard's identification of our changing relationship with symbolic meaning and the emergence of a new visual consumer culture in order to demonstrate the miseducative effects of consumerism and to highlight the ways schools have begun to acquiesce to, rather than resist, these phenomena.In doing so I hope to bring academic recognition to school commercialism as, with rare exceptions -for example, Deron Boyles and Emery Hyslop-Margison, educational theorists have shown far less interest in this trend than those seeking to profit from it.According to Alex Molnar of the Commercialism in Education Research Unit at Arizona State University, The education press accounts for only 1 percent of all references to school commercialism.Business and advertising magazines account for the remaining 99 percent.Simply put, the topic has yet to become one that managed to get on the "radar screen" of education journals in any consistent and systematic way. 1
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".