MétaCan
Menu
Back to cohort
Record W1498564171 · doi:10.18438/b8kg8w

Development of Technology Competencies for Public Services’ Staff Has Limited External Validity

2011· article· en· W1498564171 on OpenAlexvenueno aff
Jason Martin

Bibliographic record

VenueEvidence Based Library and Information Practice · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsDeskStaffingService deskReference deskHouse of CommonsComputer scienceWorld Wide WebDocumentationPublic relationsBusinessPolitical scienceMarketingLaw

Abstract

fetched live from OpenAlex

A Review of:
 Wong, G. K. W. (2010). Information commons help desk transactions study. Journal of Academic Librarianship, 36(3), 235-241.
 
 Objective - To develop an understanding of the types of technology questions asked at an information commons help desk for the purposes of staffing the desk and training. Specifically, the study looked to answer the following questions: 
 
 1. What kind of assistance do users seek from the help desk?
 2. How complex is it to handle the technology questions?
 3. What are the key competencies desirable of the help desk staff?
 
 Design - Qualitative analysis of transactions completed at an information commons help desk.
 
 Setting - A medium sized academic library located in Hong Kong.
 
 Data - 1,636 transactions completed at an information commons help desk between January 2007 and May 2009.
 
 Methods - From the opening in 2006, the staff of the information commons help desk recorded all transactions electronically using a modified version of the open source software LibStats. The author examined the transactions for roughly the second and third weeks of each month from January 2007 to May 2009 in an effort to determine the types of questions asked and their complexity.
 
 Main Results - In response to question one, 86.3% of questions asked at the help desk concerned technology; the majority of those questions (76.5%) were about printing, wireless connection, and various software operation. For question two, 82% of technology questions were determined to be of the lowest tier (Tier 1) of complexity, one-third of the questions required only “direct answers,” and 80% of questions could be answered consistently via the creation of a “knowledge base of answers for these foreseeable questions.” For question three, a list of fourteen competencies for help desk staff were created.
 
 Conclusion - With the low complexity of the technology questions asked, the creation of a knowledge base of common questions and answers, and proper training of staff based on the competencies identified in the study, an information commons could be effective with one integrated desk staffed by a librarian and paraprofessional staff member.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.967
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.558
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 head0.088
GPT teacher head0.289
Teacher spread0.201 · 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
GenreEmpirical

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
Published2011
Admission routes1
Has abstractyes

Explore more

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