The importance of a national presence for a national archives in the digital age
Bibliographic record
Abstract
This thesis examines the history and strategic importance of maintaining a regional presence for Canada’s national archives (Library and Archives Canada/LAC). If the national archives of a large federation, such as Canada, is to preserve the archival records of the Government of Canada, it must be equal to the task of providing access to records that reflect the complex and diverse character of the country and the decentralized structure of its governing institutions. Provision of archival services for Canadian federal government records is the responsibility of LAC. These records are not only created in Ottawa but in federal offices across the country. LAC requires a similar nationwide presence to ensure that every citizen of Canada has a relatively equal opportunity to access these archival records. Thus, LAC has had, since the 1980s, regional offices in various Canadian cities. These offices are responsible for federal records created in their particular region. These offices have played limited roles overall in providing LAC’s services to federal agencies and the public. At its peak, there were nine regional offices. Budget restraints have caused the closure of six. There are offices now only in Vancouver, Winnipeg, and Halifax. At the same time, however, LAC is planning to increase the visibility of its remaining offices and their ability to provide LAC services. This thesis is being written at a time of great change and promise for LAC’s regional offices. The thesis will look at the reasons for, and the development of, the national presence of LAC in these offices and what their future may be like, particularly in the digital age. The thesis argues that a national presence for a national archives is not only important in Canada but in all nations, and especially in large ones like Canada. Even in a digital age, it is necessary to have a physical presence across the entire nation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.023 |
| Scholarly communication | 0.024 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".