The Library's Role in Supporting Financial Literacy for Patrons
Bibliographic record
Abstract
Library Roles in Achieving Financial Literacy among its Patrons is a collection of articles from 25 librarians in different parts of the U.S. and Canada, each contributing 3,000-4,000 words: concise chapters with sidebars, bullets, and headers; there is an introduction. Contributors were selected for the creative potential in their topics, those that can be used in various types of libraries and that demonstrate a command of financial literacy and are able to communicate what they know to aiding users solve their financial information problems. The collection has three sections. The first provides an overview of financial literacy: what it means generally, what needs exist among library patrons, and what approaches have been tried to date. The second section deals with resources that are available in libraries, or should be made available. These include collections, skill sets in librarians, program opportunities and others. The third section is a series of case studies that demonstrate successes and best practices.
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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.039 | 0.009 |
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".