What the World Needs Now? Love as a Lens on Library and Information Work Today
Bibliographic record
Abstract
Library and information studies has yet to see a committed theoretical analysis of the social, relational, and political workings of love, as a force that both explicitly and implicitly underpins practices and rhetoric within our discipline. Understanding the “force” that is love requires analysis of social, or collective, relations. As such, love provides a distinctive lens onto structures and power dynamics that can illuminate and address divergent challenges within LIS and the world at large. This paper draws on selected literature in order to present such an analysis for the first time. La bibliotheconomie et les sciences de l'information a besoin d'une analyse theorique engagee du fonctionnement social, relationnel et politique de l'amour, comme force qui sous-tend a la fois explicitement et implicitement les pratiques et la rhetorique au sein de notre discipline. Comprendre la «force» qu'est l'amour necessite une analyse des relations sociales ou collectives. En tant que tel, l'amour fournit une lentille distinctive sur les structures et les dynamiques de pouvoir qui peuvent eclairer et relever des defis divergents au sein de la discipline et dans le monde en general. Cet article s'appuie sur une selection de litterature afin de presenter pour la premiere fois une telle analyse.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.017 | 0.034 |
| Scholarly communication | 0.022 | 0.018 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".