<?xml version="1.0" encoding="UTF-8"?>
<article article-type="Research Article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher">collnet-journal-of-scientometrics-and-information-management</journal-id>
      <journal-title-group>
        <journal-title>COLLNET Journal of Scientometrics and Information Management</journal-title>
      </journal-title-group>
      <issn publication-format="electronic">2168-930X</issn>
      <issn publication-format="print">0973-7766</issn>
      <publisher>
        <publisher-name>Taru Publications</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.47974/CJSIM-2025-06002</article-id>
      <title-group>
        <article-title>Statistical literacy and social transformation : What the literature tells us and what it doesn’t</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>Bulut </surname>
            <given-names>Elif</given-names>
          </name>
          <aff>Faculty of Economics and Administrative Sciences, Ondokuz Mayıs University, Samsun, Turkey</aff>
        </contrib>
      </contrib-group>
      <volume>19</volume>
      <issue>2</issue>
      <fpage>255</fpage>
      <lpage>277</lpage>
      <pub-date date-type="pub">
        <day>17</day>
        <month>12</month>
        <year>2025</year>
      </pub-date>
      <abstract>
        <p>Statistical literacy is a key competency for informed citizenship and data driven decision making. This study presents a bibliometric analysis of statistical literacy literature, exploring its conceptual, theoretical and social dimensions. Using co-citation, bibliographic coupling, co-authorship and keyword co-occurrence analyses on a dataset of 361 publications, it maps disciplinary perspectives and research trends. Emphasizing the societal importance of statistical literacy the study offers policy relevant insights and practical recommendations. It highlights the need for interdisciplinary collaboration to foster statistical literacy across sectors. By synthesizing theoretical frameworks and identifying research gaps the findings contribute to advancing both academic understanding and strategic implementation in education, information science and public policy.</p>
      </abstract>
      <kwd-group>
        <kwd>Statistical literacy</kwd>
        <kwd>Bibliometric analysis</kwd>
        <kwd>Social transformation</kwd>
        <kwd>Statistics</kwd>
        <kwd>Bibliometrics</kwd>
      </kwd-group>
      <custom-meta-group>
        <custom-meta>
          <meta-name>access</meta-name>
          <meta-value>open</meta-value>
        </custom-meta>
        <custom-meta>
          <meta-name>retracted</meta-name>
          <meta-value>no</meta-value>
        </custom-meta>
      </custom-meta-group>
    </article-meta>
  </front>
</article>
