Climate extraction and supply chains of data
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
The global data center industry relies on what this article defines as ‘climate extraction’. Through this peculiar but critical infrastructure for global Internet operations, a focus on Ireland reveals the entanglements of state, corporate, and environmental actors within the extractive calculations of transnational companies. Ireland has been advertised to and by data center developers because of its ‘cool’ climate while downplaying the importance of its low corporate tax rate and the government and planning system’s favorable treatment of big tech companies. Public discourses around big tech ‘greenwash’ power and contribute to a material climate (both atmospheric and infrastructural) from which value can be extracted. This is achieved by extracting for and from data circulation through the built and ‘natural’ environment. This article articulates the ways in which the spatial development of data centers as ‘strategic infrastructure’ contributes to the ongoing naturalization of capital and state power’s entanglements with the so-called natural world through technological systems.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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