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Record W4410408796 · doi:10.31274/archivalissues.10984

Publication Reviews

2012· article· en· W4410408796 on OpenAlexaboutno aff
Amy M. Moorman, Bradford Lee Eden, Christine Sharbrough, Deborah Rice, Elizabeth Novara, Eric Fritzler, Jean Dryden, Joshua Zimmerman, Kelly McElroy, Leigh McWhite, Lisa M. Schmidt

Bibliographic record

VenueArchival issues · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

To ask archivists if society is better off forgetting is a bold and heretical question.The title of this volume of essays is somewhat enigmatic, and raises questions such as: Who is forgetting?What is being forgotten?What is the meaning of forgetting?These questions are never directly answered, and the essays themselves do not explicitly address the title's question.A close reading of the introduction is required to discern the editors' goal in assembling this particular set of essays: to explore the neglect of the archival enterprise from the perspective of Canadian public policy.One word that characterizes the contents of this collection of essays is "wideranging."Co-editors Cheryl Avery and Mona Holmlund (archivist and art history professor, respectively, at the University of Saskatchewan) have assembled diverse authors from different fields to address the many issues that affect the well-being of the archival enterprise.The wide scope is reflected in the titles of the five parts: "The History of Funding," "Access and Privacy," "The Digital Age," "Accountability and the Public Sphere," and "Resource for the Present."Fortunately, the volume includes an index to improve access to the host of ideas discussed.In part one, archivists Marion Beyea and Shelley Sweeney address the inadequate level of funding for archives in Canada.Beyea recounts the development of the Canadian archival system in the 1970s and 1980s (including public funding for archival processing and professional development) and its subsequent erosion.Sweeney compares funding for archives with that for libraries and museums, and concludes that financial support, regardless of the source, will come only if archivists change their priorities to broaden their user base, demonstrate impact, raise their profile, and become active fundraisers (pp.31-33).Part two explores the tensions between the concepts of access and privacy.Archivist Jo-Ann Munn Gafuik discusses the federal access to information legislation as a tool to support both transparency in government and the role of archivists in assisting the public in making sense of the records that are preserved.David Surtees, a law professor, talks about privacy and the so-called disenfranchised who have no control over information that is collected about them.The challenges in finding the appropriate balance between access and privacy are demonstrated in Terry Cook and Bill Waiser's account of the Census Wars-a battle over the release of the post-1901 Canadian census data that pitted privacy advocates against archivists, historians, and genealogists.The Digital Age is the focus of Part three of the volume.Historians Chris Hackett and Robert Cole discuss the implications, particularly for historians and the process of historical research, of having source material digitized and on-line.Archivist Yvette Hackett (no relation to Chris) provides a succinct and insightful overview of the emergence of born-digital records, as well as the ways in which digital records necessitate archival practices different from those used to deal with analog records.Her argument that "digital records cost more" (pp.129-135) clearly articulates the imminent risk to our collective memory if we do not address the challenges of digital preservation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.457
Threshold uncertainty score0.652

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0020.001
Scholarly communication0.0110.006
Open science0.0030.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.5430.562

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 head0.081
GPT teacher head0.269
Teacher spread0.188 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2012
Admission routes1
Has abstractyes

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