MétaCan
Menu
Back to cohort
Record W2524433179 · doi:10.18438/b8z03k

Developing a Measure of Library Goodness

2016· article· en· W2524433179 on OpenAlexvenueno aff
Gregory A. Crawford

Bibliographic record

VenueEvidence Based Library and Information Practice · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsComparabilityComputer scienceGoodness of fitMeasure (data warehouse)DocumentationQuality (philosophy)Process (computing)Operations researchLibrary scienceManagement scienceData miningMathematicsEngineering

Abstract

fetched live from OpenAlex

A Review of:
 
 Orr, R. H. (1973). Measuring the goodness of library services: A general framework for considering quantitative measures. Journal of Documentation, 29(3), 315-332.
 
 Abstract
 
 Objective – To discuss the theoretical design of a measure of library quality and value that could be used across functional areas of a library in order to justify and maximize the allocation of resources.
 
 Design – This theoretical article provides background on how to conceptualize and develop a quantitative measure of library goodness.
 
 Setting – The process delineated is applicable to any library, whether public, academic, or special.
 
 Subjects – The intended audience is library management, both at the director and the department head levels.
 
 Methods – The author provided examples and questions in the development of appropriate variables.
 
 Main Results – The author presented a discussion of potential variables. These variables include library capability and utilization.
 
 Conclusion – The article concluded with a discussion of the major desiderata for an effective measure of library goodness: appropriateness, informativeness, validity, reproducibility, comparability, and practicality.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.835
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.291
Teacher spread0.262 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueEvidence Based Library and Information PracticeSame topicLibrary Science and Information LiteracyFrench-language works237,207