The Southern Agrarians: a case study in intellectualized collection development
Bibliographic record
Abstract
Purpose The purpose of this paper is to present a case study about how academic librarians can contribute to the interdisciplinary research endeavors of professors and students, especially doctoral candidates, through an intellectualized approach to collection development. Design/methodology/approach In the wake of protest movements such as the Tea Party and Occupy Wall Street, colleges and universities have begun to develop courses about these events, and it is anticipated that there will be much research conducted about their respective histories. Academic librarians can participate in those research efforts by developing interdisciplinary collections about protest movements and by referring researchers to those collections. Findings Through a case‐study approach, this paper provides a narrative bibliography about Southern Agrarianism that can help professors and students interested in the Tea Party or Occupy Wall Street movements to see their research endeavors from a new interdisciplinary perspective. Originality/value The value of this paper lies in presenting a concrete example of the way in which academic librarians can become active research partners through the work of building collections and recommending sources in areas that professors and students may not have previously considered.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.035 | 0.015 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.004 |
| 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".