"Second Life" Librarianship and the Gendered Work of Care in Technology
Bibliographic record
Abstract
This paper examines the basis for the commonly expressed sentiment that librarians have been late to adopt emerging technologies for use in library and information science practice. Using insights from science and technology studies, this sentiment is shown to be inadequately empirically warranted. The trope of the technophobic librarian is examined for clues to the importance of gendered emotional labor in effective library work, under the rubric of “customer service.” These clues lead to an examination of embodiment in the virtual world Second Life, and the emerging presence of librarians there. Using Second Life librarianship as a case study, this paper argues that embodiment is an important resource for library work, and that women’s technological labor is effaced through the trope of the technophobic librarian. Deconstructive analytical moves which collapse binary categories, yoked with methods from science and technology studies, are suggested for future fine-grained accounts of library technological practice.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.008 | 0.032 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".