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Record W1557784094 · doi:10.18438/b89s40

Staffing an Academic Reference Desk with Librarians is not Cost-effective

2009· article· en· W1557784094 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 · 2009
Typearticle
Languageen
FieldComputer Science
TopicLibrary Collection Development and Digital Resources
Canadian institutionsnot available
Fundersnot available
KeywordsReference deskStaffingPhoneDeskLibrary scienceComputer scienceWorld Wide WebManagement

Abstract

fetched live from OpenAlex

A Review of:
 Ryan, Susan M. “Reference Transactions Analysis: The Cost-effectiveness of Staffing a Traditional Academic Reference Desk.” Journal of Academic Librarianship 34.5 (2008): 389-99.
 
 Objective – To determine whether it is cost effective to staff an academic reference desk with librarians through an examination of the types of reference questions being asked and the qualifications required to answer them.
 
 Design – Content analysis of reference transaction logs and activity-based costing for reference services based on quantitative data derived from the logs.
 
 Setting – Stetson University, a private institution in the United States with an FTE of approximately 2500.
 
 Subjects – 6959 phone, email, and in-person reference transactions logged at the reference desk by four full-time and two part-time librarians.
 
 Methods – This study repurposes data originally collected to determine the frequency with which librarians turned to online versus print sources when responding to questions at the reference desk. Librarians working at the Stetson University library reference desk recorded all reference queries received in person, by phone, or by email for a total of eight months between 2002 and 2006. Data collection took place in two month intervals in fall 2002, spring 2003, spring 2006, and fall 2006. Each question and the sources used to address it were logged by the librarian. Directional questions that were not related to the library’s collections and technical questions dealing with printer or copier mechanical problems were counted, but the specifics of these questions were not recorded. It was felt that these queries would not yield data relevant to the original research question on sources used as they “did not directly relate to an information need” (391).
 
 A total of 6959 questions were logged by librarians during the four collection periods. Questions were recorded for only 4431 transactions; the remaining 2528 queries related to printer/copier problems or non-library specific directions and were described as “direction and machine: non-informational” (394). The 4431 recorded questions were then divided into four categories derived by the researcher: look-up (a search for a known item), directional (library-specific orientation to the space and collections), technology (assistance with using library technology and electronic resources), and reference. The category of reference was further subdivided into eight additional categories: catalogue search, citation help, database help, “guide to correct databases,” “personal knowledge or referral,” “quick internet search,” research, and Serials Solutions (392). “Guide to correct databases” referred to advice on the appropriate database to answer a question and serials solutions included questions that could be answered using the Serials Solutions product, such as the availability of a particular journal or article in the collection (392). Questions were assigned to the single most appropriate category by the researcher.
 
 Question categories were then mapped to “suggested staffing levels” (396). This determination was made by the researcher, and no details were given as to how the decision was made for each category. The three levels of staffing discussed were librarian, “trained student or staff,” and “well-trained staff/occasional librarian referral” (396).
 
 The cost of staffing the reference desk during the eight months captured in this study was calculated by multiplying the hours worked by each librarian by his/her individual average rate of pay across the four data collection periods. Indirect staff costs such as benefits were not included in this calculation. The average cost per reference transaction was determined by dividing the total salary costs by the total number of reference queries during the periods of study. Costs for those categories of questions best addressed by a librarian could then be determined.
 
 The actual number of librarians who participated in the study is unclear. The methodology refers to four full-time and two part-time librarians (391). However, later in the article there is reference to five full-time and three part-time librarians rather than the numbers initially stated (396). This may reflect staffing changes during the study period, with the first set of numbers referring to positions rather than individuals, but this cannot be verified with the evidence presented in the article.
 
 Main Results – It was determined that most questions asked at the reference desk during the study period could have been addressed by trained student and staff member rather than librarians. Only 11% (784) of questions logged were deemed sufficiently complex by the researcher to require the attention of a librarian. The remaining 6175 transactions (89% of all those logged) could most likely be handled by a different staffing complement. According to Ryan, approximately 74% of the reference transactions, including directional, technology, “quick internet,” and known item searching questions could have been answered by “trained student and staff” (396). Questions on catalogue searching, databases, citations, Serial Solutions, and personal knowledge/referrals, representing approximately 15% of all questions, could have been handled by experienced and knowledgeable staff with limited librarian intervention. The complexity of the question was in part judged by the number of sources required to answer it, with most (75%) answerable with just one source.
 
 The total cost of staffing the reference desk with librarians for the eight months studied was approximately US$49,328.00. A total of 6959 questions were logged during this period, resulting in an average cost of US$7.09 per reference transaction. This cost is approximate, as the exact time spent on each question was not recorded. The cost of answering “non-informational” directional and technical questions was the most significant (396). This category represented 36.3% of all questions received at the reference desk, with a total staffing cost of $17, 919.41 ($7.09 x 2528). “Information-orientated” directional and technology questions followed at 15.4% (US$7,620) and 12.4% (US$6,110.18) respectively (396). According to Ryan, questions in all three categories could be addressed by students and staff. The cost of addressing research questions, the only category requiring librarians, was US$5557.29. Research transactions were greatly outnumbered by directional and technology related questions. An average of 3.6 research questions were asked at the reference desk during the 12 hours it was open each day, compared to 20.8 directional/technical questions.
 
 Conclusion – The nature of questions logged at the Stetson University library reference desk suggests that it is inefficient to staff the desk with librarians, given the salary costs of such a staffing model and the fact that librarian’s skills may not be required to answer most of the questions posed. Since the number of questions that need a librarian is so low, Ryan suggests that alternative staffing and service models be considered, so the energies of librarians could be more effectively employed elsewhere in the organization in areas such as information literacy instruction and the development of enhanced web services. It is noted that any reorganization of reference services should be done in concert with user surveys, consultation with staff, and extensive training to prepare staff for new roles. Suggested areas for further research identified by the researcher include the quality of reference transactions in an increasingly online environment.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.920
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0020.601
Open science0.0010.000
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 head0.262
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