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Record W1854042962 · doi:10.18438/b8g597

Use and access of grey literature in special libraries may be hindered by lack of visibility and cataloguing

2006· article· en· W1854042962 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEvidence Based Library and Information Practice · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOptics and Image Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsLibrary scienceGrey literatureGovernment (linguistics)Presentation (obstetrics)PublishingCollection developmentSociologyPublic relationsPsychologyComputer sciencePolitical scienceMedicineMEDLINELaw

Abstract

fetched live from OpenAlex

A review of: 
 
 Ranger, Sara L. “Grey Literature in Special Libraries: Access in Use.” Publishing Research Quarterly 21.1 (Spring 2005): 53-63.
 
 Objective – To examine the barriers to making grey literature (literature not controlled by commercial publishers) easier to access in special libraries.
 
 Design – Interviews.
 
 Setting – Variety of special libraries (government, corporate and specialized academic) in the United States.
 
 Subjects – Sixteen librarians from fourteen organizations in Washington, Michigan and Texas were interviewed. Four of the organizations were government libraries, four were corporate libraries and five were specialized academic libraries. One of the interviews was not used because the organization did not maintain a collection of paper-based grey literature.
 
 Methods – Librarians were selected as possible interview subjects via three methods: some were previously familiar with the author; some were referred to the author by friends, family and colleagues; two candidates volunteered in response to a presentation of the project at a professional meeting. Interviews were conducted between February 2002 and May 2003. A standard set of seven questions were used, but often followed with further questions. The interviews were conducted either in the library or the librarian’s office. The interviews were tape-recorded and the answers were written down. Interviews typically lasted between fifteen and thirty minutes and asked about the current state, holdings, access and use of grey literature in the special library.
 
 Main Results – Results from the interviews suggest a wide variance in the percentage of users that access grey literature. Grey literature was used less in the corporate libraries than the academic and government libraries. The percentage of the collection made up of grey literature also varied widely between the different libraries. Reports were found to be the most popular form of grey literature, although most of the libraries reported owning conference proceedings and newsletters in addition to reports. One interesting observation found during the interviews was that most of the users of grey literature are also producers of grey literature. The librarians surveyed reported that some of the reasons for using grey literature included use in research, to write (often more grey literature), interest in the topic, for class assignments, as records of previous practices, for localized studies, and for creating models and practices. Results found that for the libraries surveyed, much of the grey literature remains uncatalogued and what has been catalogued was done using a variety of methods. Over half of the libraries surveyed had their grey literature accessible online.
 
 Conclusion – Two main reasons were cited as explanations for why grey literature was not used as much as it should be: lack of cataloguing and visibility. In many of the libraries surveyed, much of the grey literature had not been catalogued, making it difficult to find and use the resources. Reasons cited for not cataloguing grey literature include lack of time, funds and/or knowledge. As well, in many of the libraries surveyed, it was found that the holdings of grey literature were not readily visible to the users, so users were not even aware that it existed.
 
 To improve the awareness and accessibility of grey literature, the author recommends regional depositories for grey literature, international standards for cataloguing and more cooperation between special libraries.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0020.420
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 head0.026
GPT teacher head0.261
Teacher spread0.236 · 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