Santa Clara University's New ISP: Indispensible Services Provided by the Harrington Learning Commons, Sobrato Technology Center and Orradre Library
Bibliographic record
Abstract
Santa Clara University is the oldest institution of higher education in the state of California. Founded as a Catholic, Jesuit university in 1851, there are currently over 8,000 students enrolled in undergraduate, graduate and professional schools of business, law, engineering, pastoral ministries, and counseling psychology and education. The University Library, Information Technology and Media Services are grouped together in the umbrella administrative unit, Information Services, reporting to Vice Provost/CIO Ron Danielson. The nearly one hundred staff in Information Services are physically dispersed around campus in seven different locations including multiple services points. An older library was demolished in 2006 and a new $95 million dollar Learning Commons, Technology Center and Library will open in the Spring Quarter 2008. When the new building opens, all Information Services staff will be co-located, for the first time ever, under the same roof. This co-location presents many opportunities for the possible integration of services to students, faculty and staff members on campus. An Organizational Consulting Project was proposed and approved to better understand the collaborative opportunities afforded by this new building and collocation of staff. The major components of the consulting project are a literature review, a survey to Information Services staff, an external survey which was posted on the Information Commons listserv, recommendations and an annotated bibliography. The literature review highlights the best practices associated with successful mergers of Library, IT and Media Services staff to provide enhanced services to students and faculty. Frequently, these mergers result from the creation of an "Information Commons" or "Learning Commons" within an academic library setting. The services provided through an Information Commons include access to both reference and computer technology support services, high-end computer workstations loaded with productivity software, assistance with multimedia software, and the availability of a full range of scholarly research materials anytime and anywhere. Staff providing these services need thorough and ongoing training in the full range of activities they will be called upon to perform. Special care must be taken to understand the cultural differences that can divide library and IT staff which might include unique or, at least, distinct jargon, professional status, certifications, education and temperament. The Myers-Briggs Type Indicator is mentioned frequently in the literature as a means to help understand and work better with others. The leadership of a merged organization is critical and a chief information officer must possess solid political and managerial skills to help bridge differences. Mergers usually don't save money. As one chief information officer observed, "How can you save money by combining the old 'bottomless pit' [the library] with the new 'black hole' [the computer center]?" The literature review also provides an examination of the success factors with distinguish established and thriving collaborations as well as the range of staffing models that are often employed.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.008 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".