Redrawing the boundaries of societal memory, introducing a modified macro-appraisal approach at the Great-West Life Assurance and London Life Insurance companies
Bibliographic record
Abstract
This thesis examines public sector archival appraisal theories and assesses their suitability for use in the in-house corporate archives of two large Canadian insurance orporations--The Great-West Life Assurance Company and the London Life Insurance Company. Three main theories are outlined: one in which records' creators, not archivists or the public, determine a record's value; one in which research needs determine the value of records; and the macro-appraisal approach--developed by Terry Cook for the National Archives of Canada--in which an archivist appraises the importance of the function which creates the records rather than the information content of the record itself. The development of corporate archives in North America, roles required of archives by their corporate sponsors, access restrictions to repositories' records, and responsibilities of the private sector to society, compel the author to conclude that a corporate archives' responsibility is primarily to the corporation not the public. A modified macro-appraisal approach--eliminating its citizen-state component--is chosen as the most suitable appraisal method for corporate records. Histories of these corporations and the development of their archives and records management programs are offered to help to investigate the implementation of macro-appraisal and provide context. The author identifies changes to organizational structure, resources, and prevalent corporate attitudes toward archiving and records management that are needed to make macro-appraisal viable and to ensure the preservation of the corporations' archival records.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.015 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".