Hyperlink analysis of the visibility of Canadian library and information science school web sites
Bibliographic record
Abstract
Purpose The purpose of this paper is to probe the external visibility of the web sites of all seven ALA‐accredited Canadian library and information science (LIS) schools. The number of inlinks to the schools' web sites is used as an indicator of the visibility of all or some portions of the LIS web sites. Design/methodology/approach Inlinks pointing to the LIS school web sites were collected using the AlltheWeb search engine. The LIS school web pages pointed to by inlinks were manually analysed to discover visible topics and contents. Findings Four content clusters were identified by which to group the content of all the inlinked LIS school web pages. These clusters were LIS, research, home page and resources. The most visible cluster was the LIS cluster and the least visible was the research cluster. The most visible topics were student projects/activities, LIS‐related resources and course‐related information, in that order. The home page of each LIS school's web site was shown to be the single web page with the most visibility. Originality/value This was a comparative webometric study, which collected and analysed inlinks for seven Canadian LIS school web sites at two different times, 3 years apart (2003 and 2006). In the study, the ranking of visible clusters, topics and web pages from the LIS web sites were identified.
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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 | 0.004 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.052 | 0.052 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".