Bibliographic record
Abstract
Research Council of Canada very recently announced a programme of grants focused on 'Skills and Work in the Digital Economy.' In the spring of 2019, the French National Research Agency launched a Flash Call, 'Open science: research practices and open research data,' with a budget of more than two million euros. The keywords of the twenty-five selected projects are 'interoperability,' 'open data,' 'data management,' 'e-infrastructure,' and even 'impulser la science ouverte' ('boosting open science')-plenty of food for thought for the uninitiated. Digital technology could apparently give a much-needed boost to the meaning and legitimacy of the the humanities and social sciences, guaranteeing a heightened form of awareness and transferability of knowledge to non-specialized audiences, while also making it possible to create pathways between the separate territories of historians, anthropologists and other sociologists and the 'real' world. It would seem too that the digital humanities could go hand in hand with innovative teaching practices, as one might deduce from the increase since the early 2000s in the number of Master's and other postgraduate degrees with a digital profile.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.007 |
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; both teacher heads agree on what is shown here.
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".