Bibliographic record
Abstract
Why would a practicing medical librarian want to read a new edition of a text used in a required foundations class for graduate students in library and information science (LIS)? First, it has been many years since most of us were in library school. We know that our profession has changed and we all keep up as much as we can, but each of us knows some aspects of the profession better than others. Librarianship was once a profession in which change could come slowly; that is no longer possible. A current, systematic text can help us fill in some gaps in our understanding and make the intellectual connections with what we already know. Second, we all have to explain these principles to nonlibrarians from time to time. Here in one volume, we have a helpful resource that explains the rationale for them. Third, we can use it in our professional recruitment and mentoring activities. Few of us will want to read it straight through, but most will find useful sections. In short, like many medical textbooks, it is a valuable reference. Librarians, faculty, students, and employers have a wide range of expectations of what an LIS master's degree graduate should know. This text does not cover the entire curriculum, but such a foundations course usually is a prerequisite for the rest of the curriculum. It emphasizes common issues for many kinds of librarianship with brief discussions of implications for some specializations. The author is the director of the School of Library and Information Science at Kent State University in Ohio [1]. Other books by the same author from the same publisher include Hiring Library Employees: A How-to-do-it Manual and Human Resource Management in Libraries: Theory and Practice. Rubin's textbook is comprehensive and supplements topics with excellent suggestions for further reading. The writing is information dense and never rambles. The chapters cover libraries in the context of the current information infrastructure, a service perspective on information science, and the impacts and implications of technological change on libraries. Information policy is covered from a macro level (the information industry, government control) through selection, collection, reference, and access policies to a micro level with an individual client. Other chapters cover the organization of information and the organization of the institution. The book has excellent descriptions of the history and current development of the institutions, professional education, and the profession. As any good foundations text should, it includes an extensive discussion of ethics and standards. The appendixes cover major periodicals, indexes, dictionaries, and encyclopedias in the field; professional associations (including the Medical Library Association); American Library Association–accredited master's degree programs in the United States and Canada; and codes of ethics from nonlibrary information professions. (The library and information science association codes of ethics are in the main text.) The use of annual numeric data as recent as 2003 (with projections as far off as 2010) is an indicator of the currency of this edition. Topics not in the first edition from 1998 [2] include the semantic Web; Internet2; the USA Patriot Act; the Technology, Education, and Copyright Harmonization (TEACH) Act; MARC21; the Dublin Core Metadata Initiative; digital rights management; digital libraries; the Scholarly Publishing and Academic Resources Coalition (SPARC); electronic reference; and the Kellogg– Association for Library and Information Science Education (ALISE) Information Professions Education Reform (KALIPER) project. The only other current related textbook, Fundamentals of Information Studies: Understanding Information and Its Environment [3], is intended for undergraduate use and has much less emphasis on libraries.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.089 | 0.063 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".