The National Site Licensing of Electronic Resources: An Institutional Perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
While academic libraries in most countries are struggling to negotiate with publishers and vendors individually or collaboratively via consortia, a few countries have experimented with a different model, national site licensing (NSL). Because NSL often involves government and large-scale collaboration, it has the potential to solve many problems in the complex licensing world. However, not many nations have adopted it. This study uses historical research approach and the comparative case study research method to explore the seemingly low level of adoption. The cases include the Canadian National Site Licensing Project (CNSLP), the United Kingdom’s National Electronic Site Licensing Initiative (NESLI), and the United States, which has not adopted NSL. The theoretical framework guiding the research design and data collection is W. Richard Scott’s institutional theory, which utilizes three supporting pillars—regulative, normative, and cultural-cognitive—to analyze institutional processes. In this study, the regulative pillar and the normative pillar of NSL adoption— an institutional construction and change—are examined. Data were collected from monographs, research articles, government documents, and relevant websites. Based on the analysis of these cases, a preliminary model is proposed for the adoption of NSL. The factors that support a country’s adoption of NSL include the need for new institutions, a centralized educational policy-making system and funding system, supportive political trends, and the tradition of cooperation. The factors that may prevent a country from adopting NSL include decentralized educational policy and funding, diversity and the large number of institutions, the concern for the “Big Deal,” and the concern for monopoly.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.021 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it