Bibliographic record
Abstract
Abstract | When in 2011 a world-leading IT company expressed the intention to locate its infrastructure in the Swedish city of Luleå, this announcement immediately triggered future scenarios and visions of a new industrial era, economic prosperity, and changing urban life. Such anticipation was supported and shaped by municipal planning and business-management activities that soon materialized in the form of building sites, regional development strategies, and new markets. Since the actual name and operations of the IT company were kept entirely secret, the planning and implementation of “Project Gold”—as the data centre project was called locally—was as much driven by collective imaginaries as by hard facts or past experiences. This article is based on an ethnographic study that followed the implementation of Facebook’s first European data centre in Luleå. The paper analyzes different modes of data centre infrastructural (in)visibility and shows how imaginaries became influential both for implementing the cloud in Luleå and for shaping the anticipated time and space of “post-extractive modernity.” More specifically, the paper focuses on socio-technical preconditions as well as concrete practices and styles—technologies of imagination—enabling those imaginaries.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.023 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".