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| Main Author: | |
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| Format: | Recurso educativo Open Access |
| Language: | en |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://eric.ed.gov/?id=EJ1438791 |
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Table of Contents:
- Data-Driven to Avoid Soft Censorship Robbie Barber Censorship Books School Libraries Reading Material Selection Context Effect Data Use Data Collection Library Materials Soft or self-censorship is when librarians' modify their book choices, not based on a selection policy, but on the climate. To avoid getting in trouble, they choose books that will not be controversial. The result may be that their self-censorship is a greater threat to school libraries than the actual book challenges. In this article, Robbie Barber examines how a data-driven process is a solution to be sure librarians' are meeting the needs of their learners and not second-guessing themselves. The data they collect through surveys, circulation, observation, and other methods, including their self-reflection process, determines their ability to provide a variety of materials for their learners.