Open Data and Official Language Regimes: An Examination of the Canadian Experience
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
The open data moving is gathering steam globally, and it has the potential to transform relationships between citizens, the private sector and government. To date, little or no attention has been given to the particular challenge of realizing the benefits of open data within in an officially bi- or multi-lingual jurisdiction. Using the efforts and obligations of the Canadian federal government as a case study, the authors identify the challenges posed by developing and implementing an open data agenda within an officially bilingual state. Key concerns include (1) whether governments may use open data to outsource some information analysis and information services to an unregulated private sector through open data initiatives, thus directly or indirectly avoiding obligations to provide information analysis and information tools in official languages; and (2) whether the rush by governments to support the innovation agenda of open data may leave minority language communities both underserved and under-included in the development and use of open data.
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 | 0.003 | 0.000 |
| 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 | 0.001 | 0.002 |
| Open science | 0.003 | 0.002 |
| 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