The Coin of Love and Virtue: Academic Libraries and Value in a Global Pandemic
Bibliographic record
Abstract
In September 2010, the Association of College and Research Libraries released The Value of Academic Libraries: A Comprehensive Research Review and Report. The spread of the novel coronavirus and the resulting global pandemic has raised questions about the concept of value in academic libraries. How is value attributed? How does value function? What does it mean to demonstrate or prove our value? We begin with an overview and analysis of ACRL’s Value of Academic Libraries Initiative. We then provide a description and timeline of the spread of COVID-19 and the reaction of both institutions of higher education, academic libraries, professional library organizations, and individual librarians. The pandemic has created a new category of workers - “essential workers” - who provide vital services, perform maintenance work, and labor to keep infrastructures intact. The role of carework and careworkers in the pandemic helps illuminate the situation of academic librarians within regimes of neoliberal austerity. Ultimately we argue that although the discourse of library value seeks to prove library value rationally and empirically, through a lot of quantitative data, capitalism, the economy, and value are fundamentally irrational. Academic library value must be claimed politically; misrecognizing the nature of the problem and relying on commonsense understandings of value and the economic, which is what the discourse of library value has done for the past decade, goes nowhere.
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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.010 | 0.061 |
| Scholarly communication | 0.022 | 0.025 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".