User-Focused Values of Empathy, Empowerment, and Communication Are Unheralded in Previous Conceptualizations of Reference and Information Services
Bibliographic record
Abstract
A Review of: VanScoy, Amy. (2021). Using Q methodology to understand conflicting conceptualizations of reference and information service. Library and Information Science Research, 43(1), 101107. https://doi.org/10.1016/j.lisr.2021.101107 Abstract Objective – To understand how experienced librarians conceptualize reference and information service (RIS), and to determine if and to what extent these conceptualizations match existing RIS models. Design – Q methodology card sort followed by short interview. Setting – Academic, public, school, and special libraries in Slovenia, South Africa, and the United States. Subjects – Sixty-six (66) librarians from Slovenia, South Africa, and the United States. Methods – The researcher asked participants to sort 35 statements about RIS from “Least like how I think” to “Most like how I think.” The participants had the opportunity to comment on their card sort. From these card sorts, the researcher used statistical methods to generate factors describing underlying conceptualizations of RIS. These factors were compared to existing literature on RIS. Main Results – Departing from the prevailing “information provision/instruction” conceptualizations of RIS, the researcher found that most respondents conceptualized RIS according to three previously unacknowledged paradigms: 1) transformation and empathy; 2) communication and information provision; and 3) empowering and learning. Fifty-three (53) of the 66 participants loaded on to one of these three factors, i.e. sorted their cards in a similar way to other participants in that factor. Factors 2 and 3 supported existing ideas of RIS in the literature, whereas factor 1 presented a novel understanding of RIS. Common to all three factors, however, is a strong focus on the user. Conclusion – Traditional models conceptualize RIS as emphasizing either information provision or instruction. The practical judgments of experienced, working librarians, however, gesture toward different, more nuanced theoretical conclusions. Beyond the traditional poles of RIS, librarians consider empathy, empowerment, transformation, and communication as other important aspects of the RIS function.
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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 | 0.021 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.004 | 0.049 |
| Scholarly communication | 0.012 | 0.018 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".