From Mechanical Objectivity to Instrumentalizing Theory: Inventing Radio Ionospheric Sounders
Bibliographic record
Abstract
While the discovery of the ionosphere through wireless communications technology in the mid-1920s had built a close connection between atmospheric science and radio, the full-fledged use of radio waves as a geophysical probe did not start until an instrumental development occurred a few years later. This article examines this advance, which centered on the invention of radio sounders of the ionosphere. Like the earlier radio experiments on the ionosphere, the sounders bounced radio waves off the upper atmosphere and inferred its properties from the returns. But the new apparatuses contained valuable innovations. In the 1930s, researchers at American Telephone and Telegraph Company (AT&T), Britain's Radio Research Board (RRB), the Technical University of Munich, and the U.S. National Bureau of Standards (NBS) automated data recording with oscilloscopic displays and inscription gadgets. They also devised control mechanisms to synchronize the acquisition of data with the change of transmitting signals. On the one hand, such automation was consistent with Lorraine Daston and Peter Galison's "mechanical objectivity," which minimizes human interference, makes experiments repeatable, and reduces personal equations, most notably perhaps with the Bureau of Standards' automatic single-frequency sounder. On the other hand, however, the automation also embodied mechanically theory-laden experimental procedures—it instrumentalized a theory that underlay the experimental scheme. The British and Americans' sweep-frequency recorder reckoned precisely the mandate of the magneto-ionic theory, the dominant model of radio-wave propagation. The sweep-frequency recorder incorporated the magneto-ionic theory by producing an easy-to-measure critical condition that the theory had predicted.
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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 | 0.023 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.073 |
| Scholarly communication | 0.009 | 0.017 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".