Bibliographic record
Abstract
Since at least the time of Galileo, physicists have considered frames of reference, how to communicate between those frames, and how different frames may be more or less useful in a particular problem.Among other things, these frames help to define a relationship between a researcher and the system being studied and influence how the boundaries of the system are determined.As an example of the usefulness of considering frames of reference carefully, Einstein's general and special theories of relativity are ultimately about how things appear to observers in different frames.This use of frames, however, has several important, and usually unexamined, consequences.First, the observer's frame, in classical physics, always leaves her outside the system under consideration: the observer is not examined, whereas the system is exactly that which is examined.1 Second, the choice of frames helps to define a priori the important observables for a system under consideration, and it is assumed that the choice of variables is done "objectively" (i.e., all researchers will choose the same variables and measure them with identical results).Lastly, as the lens of a camera limits what the photographer sees, the (classical) choice of frame largely cuts the system off 1 It is true that both quantum mechanics and relativity begin to examine the observer.However, quantum mechanics and relativity mark the transition from classical physics to "modern physics".Despite the terminology, classical physics has all the hallmarks of philosophical "modernity" and "modern physics" really belongs more to the post-modern worldview.
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.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.058 |
| Scholarly communication | 0.015 | 0.027 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".