Editorial: Great Piles of Stuff or Piles of Great Stuff? Entrepreneurial Curation and the School Librarian
Bibliographic record
Abstract
Welcome to the 20th Anniversary issue of School Libraries Worldwide! For these last two decades, it has been our pleasure to bring you the finest school library research from across the globe. The theme of this issue, Curation: Building the Learning Resource Base through Selection, Management, and Promotion of School Library Collections, was prompted by the fact that K-12 instructional planning is changing-and continues to change very quickly. Whereas teachers were once left to their own devices, and hopefully to their school librarians, to identify and integrate high quality learning resources, the recent past of federal educational initiatives has transformed instructional materials selection from one based on pull (i.e., resources gained from colleagues, search engines, and specialized digital libraries) to one based on push (e.g., resources presented to teachers in the context of a standards and assessment linked student data systems or a digital library). This fundamental change in the way teachers base their instructional plans in the United States stems from two main forces: shift to the Common Core State Standards and Next Generation Science Standards and their accompanying shift high stakes testing based on students' aptitude for applying concepts. With these twin imperatives reinforced in federal education policy via the Elementary and Secondary Education Act authorization known as No Child Left Behind (NCLB) and the related Race to the Top (RttT) initiative, school administrators are left to make tough decisions about how to shift financial resources to ensure that their teachers have sufficient means to implement high quality instruction as defined by federal guidelines.Unfortunately, too often, school administrators have identified school librarians as surplus to their educational goals (Ellerson, 2012a; 2012b). Instead, they have relied upon commercial systems populated with fee-based resources to provide teachers' essential materials base (Maull, Salidvar, & Sumner, 2010a; 2010b). Some of these systems are operationalized as digital textbooks that represent assemblages of resources tailored to a specific learning goal, also known as digital textbooks.Many digital textbooks are based on OERs, which are teaching, learning, and research resources that reside in the public domain or have been released under an intellectual property license that permits their free use and re-purposing by others (Hewlett Foundation, 2007, p.1]. School librarians are being eliminated at a time when their expertise in identifying, organizing, maintaining, and promoting (i.e., curating) high quality Open Education Resources (OERs) could provide the content and support upon which teacher and student achievement could be based. Perhaps as a result, compliance with federal encouragements to embrace OERs has been piecemeal and slow (Porcello & Hsi, 2013).Certainly, identifying and aggregating OERs and other digital resources are two key aspects of 21st Century collection development. However, due to the sheer number of these items, curation is crucial to ensure that evolving definitions of quality are reflected in the collection (Rosenbaum, 2013).I posit that curation is an entrepreneurial activity. As Goldstein and Rodriguez (2012) pointed out, entrepreneurs are innovative problem solvers. The heritage of librarianship is inherently translational in that librarians take the position of layering information resources onto possible solutions for problems in just about any discipline. The librarian's approach is constantly fresh, constantly reinventing, and constantly injecting expertly selected information into potentially insurmountable quests for knowledge. In this way, LIS education fosters information entrepreneurialism through the development of the resource expertise enacted through curation.Moreover, the growing array of resource types demands expertise not only in identifying high quality or trustworthy resources, but also curation means recommending the right resource in both content and format. …
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.027 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".