The Chiasmus of Librarianship and Collaborative Research for Evidence Based Practice
Bibliographic record
Abstract
Introduction It is my contention librarianship will experience throughout much of the twenty-first century a profound chiasmus or flip from the universal homogeneity of values and practice currently dominating the profession, to the particularistic heterogeneity characteristic of nineteenth century librarianship. This transformation will arise out of the necessity to meet the needs of specific communities and their unique ways of knowing through the collaborative development of evidence based practice for multiple knowledge systems. The paper concludes that if evidence based practice is to make a substantive contribution to this the chiasmus of librarianship it will need to embrace research methodologies developed in collaboration with multiple communities of knowing. From particularistic heterogeneity to universal homogeneity Up to the closing decades of the nineteenth century, library practice was locally orientated to meet the needs of specific communities. As there were no professional associations or institutions promulgating national values, standards or methodology it was a time of much experimentation. Consequently, library practice was heterogeneous, responding to the needs of particular communities. This heterogeneous environment began to change as a result of the unprecedented acceleration of social, economic and technological developments during the closing decades of the nineteenth century. The creation of a political, economic and cultural mass society was in the making. One consequence of this change was the creation of a sufficient critical mass of
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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 | 0.128 | 0.155 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.011 | 0.137 |
| Scholarly communication | 0.046 | 0.043 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.017 | 0.024 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".