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Record W2560151723 · doi:10.18352/lq.10176

Library Carpentry: Software Skills Training for Library Professionals

2016· article· en· W2560151723 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLIBER Quarterly The Journal of the Association of European Research Libraries · 2016
Typearticle
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsUniversity Hospital Foundation
Fundersnot available
KeywordsCarpentrySyllabusDisciplineClass (philosophy)SoftwareEmployabilityResource (disambiguation)Medical educationProfessional developmentComputer scienceEngineering managementEngineeringSociologyPedagogyMedicineSocial science

Abstract

fetched live from OpenAlex

Librarians play a crucial role in cultivating world-class research and in most disciplinary areas today world-class research relies on the use of software. This paper describes Library Carpentry, an introductory software skills training programme with a focus on the needs and requirements of library and information professionals. Using Library Carpentry as a case study of the development and delivery of software skills focused professional development, this paper describes the institutional and intellectual contexts in which Library Carpentry was conceived, the syllabus used for the initial exploratory programme, the administrative apparatus through which the programme was delivered, and the analysis of data collection exercises conducted during the programme. As many university librarians already have substantial expertise working with data, it argues that adding software skills (that is, coding and data manipulation that goes beyond the use of familiar office suites) to their armoury is an effective and important use of professional development resource.

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)0.010
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Open science
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.730
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.053
Open science0.0080.002
Research integrity0.0000.001
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 head0.074
GPT teacher head0.336
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