Personal Papers and MPLP: Strategies and Techniques
Bibliographic record
Abstract
En 2005, Mark A. Greene et Dennis Meissner publièrent un article exhortant les archivistes à réévaluer leurs stratégies de traitement des documents d'archives afin de placer moins d'importance sur les classements et descriptions détaillées et plus sur les efforts minimaux pour rendre les documents accessibles aux chercheurs.En 2008, l'Auburn Avenue Research Library on African American Culture and History, à Atlanta, en Georgie, a octroyé une bourse du Council of Library and Information Resources afin de traiter les documents personnels d'Andrew J. Young.Les conditions attachées à la bourse exigeaient l'adoption des techniques « plus de produit, moins de processus » de Greene et Meissner.Cet article décrit l'analyse et les stratégies qui ont mené vers la décision de se servir d'une variété de niveaux de traitement pour classer les documents d'Andrew J. Young, qui couvrent plus de cinquante ans de sa vie publique et privée.Ce projet a permis au personnel des archives de mener des expériences sur une étendue de méthodes pour classer et décrire la collection, allant d'une description minimale à une description à la pièce.Une fois le projet complété, il fut découvert que la meilleure façon de traiter une collection est de ne pas se limiter uniquement à la méthode de la description à la pièce ou à celle du « plus de produit, moins de processus », mais d'employer les techniques appropriées de diverses méthodes afin de créer une stratégie adéquate et de longue durée.ABSTRACT In 2005, Mark A. Greene and Dennis Meissner published an article urging archivists to reassess processing strategies to focus less on detailed arrangement and description and more on minimal efforts to provide access to researchers.In 2008, the Auburn Avenue Research Library on African American Culture and History in Atlanta, Georgia, was awarded a grant from the Council of Library and Information Resources to process the personal papers of Andrew J. Young.The grant stipulated the implementation of Greene and Meissner's "more product, less process" (MPLP) techniques.This article describes the analysis and strategies behind the decisions made to utilize a variety of processing levels applied to the papers of Andrew J. Young, which cover more than fifty years of his public and private life.The project allowed archives staff to experiment with a range of methods to arrange and describe the collection, from minimal to item-level.Upon the completion of the project, the main lesson learned was that the best way to process a collection is not to adhere strictly to item-level or MPLP approaches but to bring together appropriate techniques from multiple approaches to create a suitable and long-term strategy.
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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 | 0.012 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.011 | 0.018 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.026 | 0.022 |
| Open science | 0.006 | 0.012 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.106 | 0.049 |
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".