Abstracter

An abstracter is a person or entity whose primary function is to create abstracts. This involves condensing, summarizing, and extracting the essential information from longer texts, documents, or bodies of work. The abstracter aims to provide a concise and accurate representation of the original material, highlighting key concepts, arguments, and findings, often used for indexing, information retrieval, or dissemination. They employ skills in critical reading, information synthesis, and effective communication to distill complex content into a shorter, manageable form. Successful abstracters maintain objectivity and avoid introducing personal opinions or interpretations beyond the scope of the source material.

Abstracter meaning with examples

• The library hired a team of skilled abstracters to process the massive backlog of scientific publications. Their job was to produce clear and informative summaries that would allow researchers to quickly identify relevant articles without reading the full text of each one. This streamlined the research process significantly. The abstracters had to be detail-oriented and well-versed in various scientific fields.
• As part of the legal proceedings, the paralegal served as an abstracter, reviewing thousands of pages of documents to create concise summaries for the lawyers. This process helped the legal team understand the core arguments and evidence, significantly aiding in the preparation of their case. The efficiency of their abstracting was crucial to winning the case.
• The journal utilizes in-house abstracters to provide brief overviews of published papers, so that the audience can easily find what interests them. They condense the key research findings and methodologies into easily digestible snippets. Accurate abstracting is extremely important for the journals reputation and helps drive readership.
• The AI company employed machine learning algorithms designed to function as abstracters. Their goal was to automatically summarize news articles and legal documents, saving human employees vast amounts of time. These algorithms are only useful if the information pulled is accurate, but the results still need to be checked by human abstracters.