Language and indexing biases may exist among Chinese-sponsored randomized clinical trials (CS-RCTs). Such biases may threaten the validity of systematic reviews.
The process of knowledge representation as well as its procedures or tools and its products are not neutral in terms of values; instead they imply moral values. In this context, bias in representation related to prejudice and discrimination, to gender issues, to dicotomic categorization in classification systems or in thesauri and to lack of cultural warrant may arise. Concerning the problem of bias in indexing languages, starting from the initial theoretical reflexions of Brey (1999), Berman (1993), Olson (1998; 2002), Lopez-Huertas Perez & Torres Ramirez (2005), Guimaraes (2006), Hjorland (2008) and Milani et al. (2009), the proposal is to present a preliminary categorization aiming at facilitating the identification of bias concerning feminine issues in indexing languages, to offer a contribution to the theoretical universe of the specific questions of knowledge organization and to present a theme to be discussed by educators and professionals in the areas of cataloging, classification and indexing. If in a society which intends to be politically correct, social attitudes towards stigmatized citizens should be modified, then, the universe of indexing languages, taken as tools of knowledge representation, is a fertile field to sow this reflexion.
The small size of institutes and publication clusters is a problem when determining citation indices. To improve the citation indexing of small sets of publications (less than 50 or 100 publications), a method is proposed. In addition, a method for error calculation is given for large sets of publications. Here, the classical methods of citation indexing remain valid.
PubMed is a primary global open-access literature research database. Articles on PubMed are indexed manually with medical subject headings (MeSH®) to facilitate more complete literature searches. We aimed to determine the length of delay from publication to MeSH® indexing for key respiratory journals and to investigate whether delays are increasing over time and whether there are country or impact-factor specific biases in indexing.
This paper presents a preliminary exploration of an actor-based model for subject indexing, which considers four types of actors: professional indexers, domain experts, casual indexers, and machine algorithms. The paper describes each of the four actors, enumerating differences in approach, training, methodology, priorities, and tools, as well as similarities and historical collaborations between actors. The paper then explores how the actor-based model for subject indexing might serve as a complement to existing models that focus on processes, methods, disciplinary norms, and cultural biases by defining and exploring the following key properties of an actor-based model for subject indexing: 1) actors are the primary drivers of subject indexing work, 2) observing and understanding many types of actors’ processes in real-life situations is as valuable as prescribing correct methods for professional subject indexing, and 3) multiple and different types of actors can perform subject analysis work and subject representation work on the same information objects, and these hybrid (multi-actor) approaches to subject indexing are explicitly supported. These key properties suggest that an actor-based model for subject indexing might open new research opportunities and encourage new hybrid and collaborative approaches to knowledge organization.
Efforts towards internationalization have become increasingly important in scientific environments. As for content-based indexing of scientific research data, however, standards leading to internationally coherent indexing which is vital for retrieval purposes are not yet sufficiently developed. Even concerning the concrete use of indexing instruments, launched by initiatives on an international scale, there are still no binding policies and guidelines.
Against this backdrop, essential criteria which internationally applicable indexing systems should meet will be outlined. These will be illustrated through the multilingual European Language Social Science Thesaurus (ELSST ), originally based on the UK Data Archive’s (UKDA) Humanities and Social Science Electronic Thesaurus (HASSET ) and ultimately developed by the Council of European Social Science Data Archives (CESSDA). Additionally, the general pros and cons of using international versus national indexing languages will be weighed using the ELSST and the Thesaurus for the Social Sciences (TSS) developed by GESIS – Leibniz-Institute for the Social Sciences. In this light, the benefit of vocabulary crosswalks for supporting a combined use of international and national indexing systems will be discussed.
The literature on assigned indexing considers three possible viewpoints—the author's viewpoint as evidenced in the title, the users' viewpoint, and the indexer's viewpoint—and asks whether and which of those views should be reflected in an indexer's choice of terms to assign to an item. We study this question empirically, as opposed to normatively. Based on the literature that discusses whose viewpoints should be reflected, we construct a research model that includes those same three viewpoints as factors that might be influencing term assignment in actual practice. In the unique study design that we employ, the records of term assignments made by identified indexers in academic libraries are cross-referenced with the results of a survey that those same indexers completed on political views. Our results indicate that in our setting, variance in term assignment was best explained by indexers' personal political views.
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