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Record W223002631

A Guide to Library Research in Music

2009· article· en· W223002631 on OpenAlexaboutno aff
Melissa Ursula Dawn Goldsmith

Bibliographic record

VenueFontes artis musicae · 2009
Typearticle
Languageen
FieldComputer Science
TopicLibrary Collection Development and Digital Resources
Canadian institutionsnot available
Fundersnot available
KeywordsSubject (documents)MusicologyMusic educationLiteracyVisual artsSociologyLibrary scienceComputer scienceArtPedagogy
DOInot available

Abstract

fetched live from OpenAlex

A Guide to Library Research in By Pauline Shaw Bayne. Lanham, MD, Toronto, and Plymouth: Scarecrow, 2008. [xiv, 275 p. cloth: 978-0-8108-648-0. $60; paper: ISBN 978-0-8108-6211-1. $35.00] Although the author explains that this book is written not only for graduates in music but also for motivated undergraduates and independent learners (p.i), this research guide is accessible to everyone interested in music research or writing about music. Ambitious and concisely written, A Guide to Library Research in Music will undoubtedly be a valuable resource for music librarians and music scholars in need of updating their knowledge; a worthwhile preparation tool for music graduate students who will be tested on music resources or source studies; and a helpful instruction guide for educators teaching music research and/or music information literacy. author makes several assumptions about her audience. first is that, while readers may already have acquired knowledge of individual call numbers, they do not necessarily understand call number patterns or how to browse nearby books; the second is that readers have already used Google and that most have used library catalogs. assumption that the audience is primarily music graduate students at the beginning of their careers is the same as two contemporary books on the subject, Jane Gottlieb's Music Library and Research Skills (Prentice Hall, 2008) (reviewed in this issue of Fontes) and Laurie J. Sampsel's Music Research: A Handbook (Oxford UP, 2008) (reviewed in Fontes, 2009:1). book is divided into three parts: The Course: Music Research and Writing, How to: Discover and Use Resources, and Resources: Literature of Music. Most readers will need to start with the Short Course. More seasoned scholars will be able to skip around comfortably. In the first part, Bayne gives several compelling reasons for doing music research: music graduate students need to evolve from consumers of music to scholarly contributors; for any given topic, they need to know the benchmark resources and primary documents; they need to acquire survival skills for graduate study; they need to research independently. Musicians (and future music scholars) can use this Course to develop a context for their musical expression (p.3). In these initial chapters, readers are introduced to various staples of research: the three stages of the research process (developing a topic, gathering and evaluating resources, and writing), reference books (bibliographies, dictionaries, and encyclopedias, among others), union catalogs, indexes, and journal databases. Though her focus is on music research, Bayne also introduces readers to multidisciplinary resources. In contrast to Sampsel and Gottlieb, Bayne focuses more on the research process and lifelong learning goals. Sampsel, however, is more clear than Gottlieb on distinguishing both the general and the music research process. Chapter 5 offers a case study (research focusing on Chopin's piano music), including the formation of a thesis statement. Chapters about scholarly writing conclude this section, with information on citation formats, copyrights and permissions, examples of writing (including abstracts, literature reviews, program notes, and theses, among others) and various style formats. Gottlieb, in contrast to Bayne and Sampsel, provides more information about editing. Part 2 goes into further depth, exploring where to find different kinds of information, how to evaluate for authority, and how to identify the best sources. Search strategies dominate these chapters. These include browsing bookshelves, improving the effectiveness of online searching in any source by knowing the structure of the database, and understanding the difference between keywords and controlled vocabulary, such as Library of Congress Subject Headings (LCSH) Also highlighted: knowing when to employ Boolean logic; learning about other sources through bibliographies, works-cited lists and citation indexes; using a works list to locate information in thematic catalogs; locating digital content, using metasearch engines and penetrating the hidden web. …

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.180
Threshold uncertainty score0.604

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0030.001
Scholarly communication0.0080.008
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1800.201

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 head0.051
GPT teacher head0.304
Teacher spread0.252 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2009
Admission routes1
Has abstractyes

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