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
Abstract: In this article we explore what the exploding world of humanities and social science research infrastructures might mean for teaching and research in the discipline of history. We focus closely on one example, that of the Canadian Century Research Infrastructure Project (ccri). This interdisciplinary and multi-university project has constructed an infrastructure composed of microdata from the nominal-level Canadian censuses from 1911 through 1951. In addition to compiling information on approximately 2 million individuals, the ccri created a database of contextual data and a gis database. The combination of these three levels makes this infrastructure unique in the world. The ccri can be used in conjunction with Canadian census databases now being constructed or already completed for Canada from 1851 to 2001. As well, the ccri has been constructed in ways that will facilitate cross-national explorations with the United States, the United Kingdom, and several other North Atlantic countries. We suggest that the ccri can best be appreciated when situated within the current proliferation of research infrastructures across the humanities and the social sciences. We argue that these infrastructures are liberating for historians and, collectively, represent new horizons for professional activity. It would be a disservice to themselves, their students, and their profession if historians ignored these expanding horizons.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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