Bibliographic record
Abstract
Objectives – The purpose of this review is to examine the development of embedded librarianship, its multiple meanings, and activities in practice. The review will also report on published outcomes and future research needs of embedded librarian programs. Methods – A search of current literature was conducted and summarized searching PubMed, CINAHL, Library, Information Science & Technology Abstracts (EBSCO), Academic Search Complete, and ERIC (EBSCO) through August 23, 2012. Articles were selected for inclusion in the review if they reported research findings related to embedded librarianship, if they provided unique case reports about embedded librarian programs, or if they provided substantive editorial comments on the topic. Relevant study findings were assessed for quality and presented in tabular and narrative form. Results – Currently, there is disparity in how embedded librarianship is being defined and used in common practice, ranging from embedding an online component into a single course to full physical and cultural integration into an academic college or business unit of an organization. Activities of embedded librarians include creating course integrated instruction modules for either face-to-face or online courses, providing in depth research assistance to students or faculty, and co-locating within colleges or customer units via office hours for a few hours to all hours per week. Several case reports exist in the recent literature. Few high quality research studies reporting outcomes of librarians or library programs labeled as embedded exist at this point. Some evidence suggests that embedded librarians are effective with regards to student learning of information literacy objectives. Surveys suggest that both students and faculty appreciate embedded librarian services. Conclusion – Most published accounts discuss librarians embedding content and ready access to services in an online course management system. A few notable cases describe the physical and cultural integration of librarians into the library user environs. Future research using valid quantitative methods is needed to explore the impact of large scale, customized, embedded programs.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.020 | 0.026 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".