Bibliographic record
Abstract
"China became the world's larges economy in 2014." "UK GDP grew by 0.1% in the first quarter of 2018." "In the Eurozone, inflation as measured by the Harmonized Index of Consumer Prices was up 1.4% in March 2018 compared to the previous March.” Any scanner of websites that cover business news can read statements like these on any day of the week. Each statement relies on modern economic statistics using the System of National Accounts (SNA) as their basis. This chapter briefly outlines how the SNA came to have such powerful (if background) role. Further, it discusses some of the many criticisms leveled at the SNA, and particularly at Gross Domestic Product, its centerpiece. These criticisms fall into two groups. The first group raises doubts about how accurately GDP is measured. The second is more about the relevance of GDP (and the SNA) as a guide to policy. Even if GDP is measured accurately, is it measuring anything which thoughtful people should be interested in?
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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.013 |
| Insufficient payload (model declined to judge) | 0.021 | 0.011 |
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".