Practices in Progress: The State of Reappraisal and Deaccessioning in Archives
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
In the spring of 2017, the article authors conducted a survey of archival institutions in the United States and Canada regarding current reappraisal and deaccessioning practices. The first of its kind in the United States, the survey gathered quantitative data regarding how, why, and which archival repositories reappraise and deaccession. This article describes the survey method, questions asked, and data collected, and provides an analysis of the results. The authors sought to learn if resources influence these practices; what, if any, policies and guidelines exist locally; how the processes are carried out; how archivists perceive ethical concerns commonly associated with these practices; and what benefits and consequences result from reappraising and deaccessioning. They found that reappraising and deaccessioning are common practices throughout a variety of institutions and result in positive outcomes. However, misunderstanding remains about these practices, and institutions may not always be conducting these practices in an ethical and responsible manner.
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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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