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Record W2979382472 · doi:10.14288/1.0348266

Roundtable on the "Future of RAD (Rules of Archival Description)"

2017· article· en· W2979382472 on OpenAlexaboutno aff
Lisa Glandt, Richard Dancy

Bibliographic record

VenuecIRcle (University of British Columbia) · 2017
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsnot available
Fundersnot available
KeywordsComputer sciencePolitical science

Abstract

fetched live from OpenAlex

The Canadian Council of Archives (CCA) has been tasked to develop a plan to update and revise the Rules of Archival Description (RAD) and are seeking input from members of the Canadian archival community. Since 2008 there have been no revisions to the standard and it time to deal with the descriptive reality of digital records (both digitized and born-digital) in archives. The goals of this revision include aims to: - Align RAD with international archival descriptive standards - Clearly articulate the relationship of RAD to relevant standards in other allied professions (libraries, museums, galleries, digital preservation). - Ensure that RAD meets the descriptive requirements of both analogue and digital archival material. - Make RAD accessible to a range of institutions with varying levels of professional staffing. - Ensure any new standard is backwards-compatible with the current version of RAD. Richard Dancy from the Canadian Committee on Archival Description (a Committee of the CCA) participated in this discussion to provide some background on the project and help facilitate discussion on questions including: 1. What are the strengths and weaknesses of RAD in its current form? - Revision would aim to preserve and build on existing strengths. 2. What should be the scope of the standard? - RAD's approach was to be a "one-stop shop" for description at all levels in all media, is this still our aim? Contrast ISAD(G) and DACS that focus on aggregate levels of description and leave archivists to look to external media-specific standards for item-level description. - Should RAD focus only on description or should it take in other functions, e.g. accessioning, arrangement, administrative and preservation metadata? should these be dealt with separately? If separate, what are the relationships? - Does RAD need a data model to underpin the standard? This would identify the entities involved in description, their attributes and their relationships. The data modelling approach was the basis for the thorough overhaul of the librarians' cataloguing standard (RDA replacing AACR2). The ICA is currently undertaking the development of a conceptual model for archival description (see The Expert Group on Archival Description) 3. What form should "alignment" with international standards take? - Should RAD adhere closely to the ICA standards in terms of structure and data elements or is it acceptable to have a minimal set of elements in common but follow a different structure? - Are there deficiencies in the international standards that RAD should seek to remedy? 4. What is the best form for governance of the standard? - Within an archival network pressed for resources, which is the body best able to assume responsibility for maintaining the standard? 5. How should consultation proceed and who should be consulted? - What are the best ways to engage the perspectives of the various groups including Archivists, Archives advisors, Archival educators in academic archival programs, Digital preservation specialists, IT developers, Archives users, Archives creators, Librarians and Curators

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.217
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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