Bibliographic record
Abstract
This paper considers how the physical spaces of academic libraries actively assert the belief of intellectual pursuit upon users. Taking up Thomas Gieryn’s concept of “truth-spots,” this paper argues that the academic library is particularly effective at encapsulating and expressing this pursuit through its own spatial configurations. Library spaces achieve this through the manipulation of time, spatial gathering and separation, an imposed order, exposure and obfuscation, as well as the library’s unique or standardized configurations. This paper invites us to think about the library’s metaphysicality in terms that connect abstract beliefs to the library’s physical materials and spaces. The purpose of this paper is to identify the subtle, yet powerful, spatial changes occurring in recent efforts to reconfigure academic library spaces. The implications of such a consideration may aid to inform future (re)designs of library spaces.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.034 |
| Scholarly communication | 0.033 | 0.024 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.031 | 0.014 |
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".