Documentation as Data Rescue: Restoring a Collection of Canadian Health Survey Files
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
BackgroundIn Canada, most nationally representative survey data is collected by Statistics Canada, our national statistical agency.Statistics Canada data are generally considered to be of high quality, and the agency has long been the primary source for nationally representative surveys of the Canadian population.In American terms, Statistics Canada -which takes the straightforward, if acronym-limiting, Canadian standard for naming federal agencies with a guiding noun followed by "Canada"roughly takes the place of the Census Bureau, the Bureau of Labor Statistics, the National Center for Health Statistics, and the Center for Education Statistics, as well as collecting data on behalf of a number of other departments and agencies.Once collected, data are published through several outlets including the Data Liberation Initiative, a program in which data files are processed by Statistics Canada into formats suitable for use by researchers and students, and then released to a country-wide network of librarians and library representatives for distribution at their respective academic institutions.However, as a single agency with a broad mandate in a very large country with a relatively small population base, they are not able to collect, process, and release nearly as much survey data as researchers might wish.In addition, other government agencies also maintain large primarily administrative data collections to support their own operations.These collections generally do not make it into the Statistics Canada-to-university data pipeline and at one point were largely inaccessible.In 2011, the Government of Canada launched an open data pilot, a move that was applauded by data librarians and researchers across Canada as well as internationally.An open data portal soon provided access to thousands of geospatial and economic datasets, and in 2012 the pilot became a permanent program. 1 In 2014, the Canadian Directive on Open Government came into effect, requiring that data be "released in accessible and reusable formats." 2 Soon departments ranging from Agriculture and Agri-Food Canada to Veterans Canada began uploading data collections to the portal.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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