The Reference Interview: Connecting in Person and in Cyberspace: presentations and responses from the RUSA president's program, 2002 ALA Annual Conference, Atlanta, June 17, 2002
Bibliographic record
Abstract
Good afternoon, this is a reference librarian. May I help you? Variations on this greeting have been uttered by librarians for over a century as the first step in the ref erence interview. And over that century, thousands upon thousands of people have been able to find the in formation they need with the assistance of the reference librarian, children's services librarian, reader's advisory librarian, or other user services librarian. During that century, the modes of access to an in formation professional have increased in number and diverged into many communication channels. amount of information available has multiplied thou sands-fold. But when one looks at the fundamentals, some basic questions arise. profession must ask it self what has changed in the interaction beyond the communication media. Are the patrons who are asking questions in 2002 different in kind or character from the ones who were asking questions in 1952? Have the goals of the reference interview changed since 1932? Is the reference interview still necessary? For some reference librarians, doing reference work without a properly conducted interview would be sim ilar to trying to drink tea without a cup. One imagines that it might be possible but feels no desire to put the notion to a test. For other reference librarians, reference on the fly?that is, responding to the question as posed?is as natural as Rollerblading; a skill that one spends some time learning but which then allows you to be faster and more responsive. In the pieces that follow, Catherine Sheldrick Ross, dean of the faculty of information and media studies at the University of Western Ontario and Jana Ronan, in teractive reference coordinator, RefeXpress, at the Uni versity of Florida address the topic The Reference Interview: Connecting in Person and in Cyberspace. These authors look at the role of the reference inter view in the more traditional reference encounter and in the virtual realms of Web-based reference services. In their reaction pieces, Kathleen Kern, reference librarian at the University of Illinois at Urbana-Cham paign, and David Tyckoson, head of reference, Califor nia State University at Fresno, share their perspectives on the reference interview in the context of the Ross and Ronan pieces. 2002 RUSA President's Program Committee Kathleen Kluegel, Richenda Wilkinson, Gary Cornwell, Judith Smith, and Carol Tobin, RUSA president?invite readers to explore these issues with the authors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".