Graduate Students Reference Open Access Content in Literature Review Assignments
Bibliographic record
Abstract
A Review of: Allen, E. J., & Weber, R. A. (2014). The library and the web: Graduate students’ selection of open access journals for empirical literature searches. Journal of Web Librarianship, 8(3), 243-262. http://dx.doi.org/10.1080/19322909.2014.927745 Abstract Objective – This study seeks to understand to what degree education graduate students cite open access, peer-reviewed journals in their coursework and whether patterns of open access referencing change over time. Design – Longitudinal reference list analysis. Setting – Public university in the United States of America. Subjects – Reference lists collected from final literature review papers in a graduate-level education class (n = 382). Methods – The authors collected reference lists from final literature review papers in a graduate-level education class for a nine-year time frame from the 2005 to 2013 academic years. The authors analyzed 2,594 reference entries from the 382 reference lists in the sample. The authors organized reference entries into spreadsheets for analysis, creating one spreadsheet per class section and sorting references by type (e.g., book, journal article, website, etc.) and source. The authors also created a cumulative list of journal titles that they analyzed for open access status and how often the journals appeared in the sample. Other information collected about each journal included "ISSNs, national origin, journal sponsorship, frequency and years of student usage, presence of empirical research, [and] peer review status" (p. 249). Finally, the authors organized open access journals into the following four categories based on their access method: • Category A "OA Platform and Publisher" • Category B "Publisher Only" • Category C "Delay or Hybrid from Host or Publisher" • Category D "Subscription Based, but Self Archived" (p. 249) Main Results – A total of 594 unique journals appeared in reference lists over the study period, and 11.5% (n=68) of the total were open access journals. Of the open access journals, 96% (n=65) included original research articles, and the majority (n=51) fell into Category A "OA Platform and Publisher." Nine, six, and two journal titles fell into categories B, C, and D, respectively. The authors found no pattern or change in the use of open access titles during the nine-year study period. Open access journals appeared in reference lists an average of 14 times per year with the highest usage observed in 2009. Conclusion – The results show that graduate students in the sample used a range of open access journals. The presence of open access resources in reference lists signals that students may use both library subscription databases and open web search tools to complete their literature review assignments. The authors suggest potential reasons why open access use did not grow during the study period, including a possible mismatch between student research interests and the topics present in open access titles, the lack of discussion about open access publishing during library instruction, or student satisfaction with the resources provided through library-sponsored subscriptions. Librarians are encouraged to include high-quality open access resources within their catalogues or other electronic resources to increase open access discoverability and to include popular open web search tools as a means to retrieve open access materials during information literacy instruction.
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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 | 0.097 | 0.349 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.032 | 0.023 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.076 | 0.042 |
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".