Measuring the new economy: Industrial classification and open source software production
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
We analyze the way in which the North American Industry Classification System (NAICS) handles the categorization of open source software production, foregrounding theoretical and political aspects of knowledge organization. NAICS is the industry classification scheme used by the governments of Canada, Mexico and the United States to carry out their respective economic censuses. NAICS is considered a rational system that uses the underlying economic principle of similar production processes as the basis for its classes. For the Information Sector of the economy, as formulated in NAICS, a key production process is the acquisition and defense of copyright. With open source, copyleft licensing eliminates copyright acquisition and protection as major production processes, suggesting that the open source software industry warrants a separate NAICS category. More importantly, our analysis suggests that NAICS cannot be understood as a taxonomy of objective economic activity but is instead a politically and historically contingent system of data classification.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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