Earth Observation and Signal Territories: Studying U.S. Broadcast Infrastructure through Historical Network Maps, Google Earth, and Fieldwork
Bibliographic record
Abstract
This article engages with three different modes of Earth observation—historical network maps, Google Earth interfaces, and fieldwork—to develop the concept of “signal territories” and elucidate a critical approach for studying U.S. broadcast infrastructure. This approach: 1) highlights physical infrastructures—technological hardware and processes in dispersed geographic locations—as important sites for historical and critical analysis in media and communication studies; 2) explores multiple modes of infrastructure representation—ranging from cartography to phenomenology, from hand-drawn maps to digital interfaces, from circuit diagrams to site visits; and 3) foregrounds the biotechnical aspects and resource requirements of broadcast infrastructures, probing their dynamic operations and complex materialisms. Engaging with what Richard Maxwell and Toby Miller call a “materialist ecology” of media, the article explores what is at stake in understanding media infrastructures from up close and afar.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".