除了识别混合方法研究中的新兴主题:经济指数的作用:主题赫芬达尔-赫希曼指数和主题集中度

A. Onwuegbuzie
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引用次数: 0

摘要

量化技术的正式使用已经并将继续对混合方法研究领域做出宝贵贡献,其灵感来自Miles和Huberman(1984)在20世纪80年代所谓的范式战争最激烈时期出版的开创性的第一版书。然而,不幸的是,直到最近,绝大多数量化都涉及基于描述性的量化,而很少关注更先进的量化类型,包括基于探索的量化、基于测量的量化和基于推理的量化,正如Onwuegbuzie(出版中)和Onwuegbuzie和Johnson(2021)所描述的那样。然而,这些量化形式有助于提高混合方法研究中元推理的质量,从而增强意义的形成过程。考虑到加强意义形成过程的目标,本期社论的目的是展示两个经济指数,赫芬达尔-赫希曼指数和集中度比率,可以帮助将经过基于描述性量化的突发主题置于情境中——产生我所称的主题赫芬达尔-赫希曼指数和主题集中度。特别是,在逐步详细描述了这两个经济指标后,我用实际数据来说明这些指标不仅可以作为额外的描述性定量,而且可以导致探索性定量和推理性定量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Beyond Identifying Emergent Themes in Mixed Methods Research Studies: The Role of Economic Indices: The Thematic Herfindahl-Hirschman Index and the Thematic Concentration Ratio
The formal use of the technique of quantitizing has made, and continues to make, a valuable contribution to the mixed methods research field, inspired by the groundbreaking first edition of Miles and Huberman’s (1984) book that was published during the height of the so-called paradigm wars of the 1980s. However, unfortunately, until very recently, the overwhelming majority of quantitizing has involved descriptive-based quantitizing, and scant attention has been paid to more advanced types of quantitizing, which include exploratory-based quantitizing, measurement-based quantitizing, and inferential-based quantitizing, as described by Onwuegbuzie (in press) and Onwuegbuzie and Johnson (2021). Yet, these forms of quantitizing help to enhance the quality of meta-inferences in mixed methods research studies, which, in turn, enhance the meaning-making process. With this goal of enhancing the meaning-making process in mind, the purpose of this current editorial has been to demonstrate how two economic indices, the Herfindahl-Hirschman Index and the Concentration Ratio, can help to contextualize emergent themes that have been subjected to descriptive-based quantitizing—yielding what I term as a Thematic Herfindahl-Hirschman Index and the Thematic Concentration Ratio. In particular, after describing in detail these two economic indices in a step-by-step manner, I use real data to illustrate how these indices not only can serve as additional descriptive-based quantitizing, but also can lead to exploratory-based quantitizing and inferential-based quantitizing.
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