Bibliographic record
Abstract
This paper proposes an LIS research paradigm by which the transactional relationships between knowledge organization systems (KOS) and external scholarly discourses may be identified and examined. It considers subject headings as discursive acts (or Foucauldian “statements”) unto themselves—in terms of their materiality, rarity, exteriority, and accumulation—arising from such discourses, and which, through their usage in library catalogues and databases, produce their own discursive and non-discursive effects. It is argued that, since these statements lead through their existence and discovery (or absence and neglect) to the creation of further texts, then potentially oppressive discursive formations may result where marginalized knowledges are concerned. The paper aims to better understand these processes in scholarly discourses—and the role of libraries therein—by examining recent examples in the LIS literature regarding matters of race and gender, and which are suggestive of this emergent paradigm.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.038 |
| Scholarly communication | 0.021 | 0.029 |
| Open science | 0.002 | 0.024 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".