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
This report presents new evidence about occupations requiring artificial intelligence (AI)-related competencies, based on online job posting data and previous work on identifying and measuring developments in AI. It finds that the total number of AI-related jobs increased over time in the four countries considered – Canada, Singapore, the United Kingdom and the United States – and that a growing number of jobs require multiple AI-related skills. Skills related to communication, problem solving, creativity and teamwork gained relative importance over time, as did complementary software-related and AI-specific competencies. As expected, many AI-related jobs are posted in categories such as “professionals” and “technicians and associated professionals”, though AI-related skills are in demand, to varying degrees, across almost all sectors of the economy. In all countries considered, the sectors “Information and Communication”, “Financial and Insurance Activities” and “Professional, Scientific and Technical Activities” are the most AI job-intensive.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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