Corralling Web 2.0: Building an Intranet That Enables Individuals
Bibliographic record
Abstract
The days of top-down communication and controlled internal messages at a library organization are—or should be—behind us. Modern libraries must be fluid and flexible organizations with equally nimble internal communication infrastructures in place to keep up with the fast-paced environments that have been created in these organizations. As is the case at many institutions, McMaster University Library (about 100 employees) put a great deal of effort into public-facing resources and content, while the library intranet languished as an afterthought. Static Web pages were haphazardly created and linked to from the site's index page. As the site grew, the lack of global navigation, search functionality, and clarity about content ownership led to a large, confusing collection of pages that was increasingly difficult to maintain. In 2009, a project was undertaken to redesign the staff intranet and implement Drupal, an open-source content management system, to power the new site. This case study outlines the issues faced with the former intranet, requirements gathering, staff feedback, and usability tests performed to inform the redesign, site architecture, and Drupal modules implemented, features and benefits of the redesigned intranet, the use of the new intranet to corral existing Web 2.0/social media channels, governance, evaluation, and lessons learned from the project. Future phases of the project will focus on integrating other internal communication tools used by staff in their day-to-day work, including internal file-sharing drives, staff e-mail and instant messaging platforms, meeting scheduling software, and external document sharing tools such as Google Docs.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".