The Factories of the Past Are Turning Into the Data Centres of the Future
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
Abstract | This essay traces the history and geography of data’s materiality by examining the transformation of industrial building stock in Chicago to serve the needs of the data industry. Using contemporary and archival photographs as entry points, the paper unpacks the rise of an information-based economy in relation to the decline of an industrial economy. Buildings where workers once processed checks, baked bread, and printed Sears catalogues now route packets of information and host servers engaged in financial trading. Thus, contained within the physical transformation of some of Chicago’s buildings is a larger historical and geographical narrative about the uneven development of capitalism. This historical view reminds us that infrastructure is, and always has been, political. Résumé | Cet essai retrace l’histoire et la géographie de la matérialité des données en examinant la transformation des bâtiments industriels à Chicago pour répondre aux besoins de l’industrie des données. En utilisant des photographies contemporaines et d’archives comme point de départ, le texte explore la montée d’une économie axée sur l’information par rapport au déclin d’une économie industrielle. Les bâtiments où les travailleurs ont autrefois traité des chèques, cuit du pain, et imprimé les catalogues Sears, transmettent maintenant des paquets d’information et hébergent des serveurs impliqués dans les échanges financiers. Ainsi, à travers la transformation physique de certains bâtiments de Chicago, il existe un vaste récit historique et géographique à propos du développement inégal du capitalisme. Ce point de vue historique nous rappelle que l’infrastructure est, et a toujours été politique.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.003 | 0.001 |
| 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