Bibliographic record
Abstract
Though considered by some to represent a major break with LIS education, Schools of Information ('iSchools') might better be seen as representative of efforts to extend concerns with information and human users beyond the agency model of traditional LIS approaches. In this paper, the key attributes of iSchools are identified in terms of intellectual coverage, interdisciplinarity, and research commitment. Rather than formally distinct from LIS programs, iSchools are considered exemplars of a type of program into which more LIS programs might evolve. Keywords: iSchools, research orientation, LIS education, curriculum coverage Introduction In its broadest sense, [information science] stands for the systematic study of information and may include all or any combination of the academic disciplines discussed in this volume. (Machlup and Mansfield, 1983, p. 18) Schools of Information have proliferated since Machlup and Mansfield's seminal book, particularly over the last decade. Such has been the growth of iSchools in the early decades of this century that it is perhaps difficult now to appreciate fully the consternation arising from the announcement of school name changes in the late 1990s and early 2000s, first by the University of Michigan, and then by the University of Washington and the University of Texas, Austin. Since then, many other schools have modified, abbreviated, or completely changed the names of their programs to reflect a growing recognition of the intersection of people, information, and technology as the core of our concerns. Currently, among the ALA-accredited LIS programs, over 30% use the general School of Information or Information Studies names, with the majority of these having dropped the word 'Library' at some point in the last two decades. Even though the iSchool community's origins can be traced to a small group of U.S. schools that offered ALA-accredited degrees in the late 1980s (the so-called 'gang of three' consisting of Rutgers, Syracuse, and Pittsburgh; later the 'gang of four' with the addition of Drexel), the emergence of a national information school community involved both renaming and the creation of new programs. By the time the iSchool group had grown to 10 schools in 2003, it had admitted two 'green field' programs - new academic units created especially for the study of information - at Indiana University (where a School of Informatics was created despite the existence there of a longstanding program in LIS), and at Penn State University, which created its own College of Information Science and Technology in 1999. There has been growth in information related programs beyond North America also.The iCaucus, an international group of schools who gather under the 'information school' umbrella, now numbers 33 members, and includes a diverse range of programs, mainly from the U.S. but including schools in Australia, the UK, Canada, China, Denmark, Finland, Germany, Ireland, and Singapore. In sum, the idea of an 'iSchool' has evolved to the point where a significant number of universities, including those hosting 14 of the top 1 5 LIS programs from the most recent US News and World Reports Rankings, support an 'iSchool', and new schools are being created, formed from mergers, or renamed continually. The history of the iSchool movement is covered in detail in Larsen (2009), while Olson and Grudin (2009) offer an overview of the phenomenal rise of information schools in leading research universities in the US, with emphasis on the role of the annual iConference (first held in 2005 at Penn State) in cementing identity and common purpose. The latter authors asked if the emergence of iSchools was permanent or a passing fad, concluding that most likely, the serious and scholarly study of information was only in its infancy. In the present article I will take a different tack, seeking to outline what makes a school an 'iSchool' in order to shed light on the realities and aspirations of what some of us regard as a unique form of academic unit. …
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.038 | 0.014 |
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".