{"id":{"repo_id":"denver","oai_identifier":"oai:digitalcommons.du.edu:etd-2795"},"canonical_url":"https://search.dev.ndltd.org/etd/denver/oai:digitalcommons.du.edu:etd-2795","repository":{"repo_id":"denver","name":"University of Denver","base_url":"https://digitalcommons.du.edu/do/oai/"},"display":{"title":"Is the Reliability of Objective Originality Scores Confounded by Elaboration?","abstract":"<p>The increased use of text-mining models as a scoring mechanism for divergent thinking (DT) tasks has sparked concerns about the ways in which automated Originality scores may be influenced by other dimensions of DT, especially Elaboration. The debate centers around the question of whether too much variance in automated Originality scores is accounted for by the number of words a participant uses in a response (i.e., Elaboration), and, thus, how the influence of Elaboration can affect the reliability of Originality scores. Here, a partial correlation analysis, in conjunction with text-mining and psychometric modeling, is conducted to test the degree to which the reliability of Originality scores produced via a freely-available text-mining system is dependent on the variance explained by Elaboration. Findings reveal that, when modern methodological recommendations for text-mining Originality scoring are applied, the reliability of Originality scores estimated by the GloVe 840B text-mining system is not meaningfully confounded by Elaboration. I conclude that, even when the variance attributed to Elaboration is partialled out, this method is capable of providing reliable Originality scores.</p>","abstract_html":"&lt;p&gt;The increased use of text-mining models as a scoring mechanism for divergent thinking (DT) tasks has sparked concerns about the ways in which automated Originality scores may be influenced by other dimensions of DT, especially Elaboration. The debate centers around the question of whether too much variance in automated Originality scores is accounted for by the number of words a participant uses in a response (i.e., Elaboration), and, thus, how the influence of Elaboration can affect the reliability of Originality scores. Here, a partial correlation analysis, in conjunction with text-mining and psychometric modeling, is conducted to test the degree to which the reliability of Originality scores produced via a freely-available text-mining system is dependent on the variance explained by Elaboration. Findings reveal that, when modern methodological recommendations for text-mining Originality scoring are applied, the reliability of Originality scores estimated by the GloVe 840B text-mining system is not meaningfully confounded by Elaboration. I conclude that, even when the variance attributed to Elaboration is partialled out, this method is capable of providing reliable Originality scores.&lt;/p&gt;","abstract_has_math":false,"creators":["Maio, Shannon Marie"],"institution":null,"degree_name":"M.A.","degree_level":"Masters Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Denis Dumas","Peter Organisciak","Garrett Roberts","Jesse Owen"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-01-01T08:00:00Z","date_published":"2020-01-01T08:00:00Z","updated_at":"2026-07-24T02:02:19Z","subjects":["Divergent thinking","Elaboration","Originality","Reliability","Text-mining model","Psychology","Statistical Methodology","Statistics and Probability"],"languages":["en"],"rights":["<p>Copyright is held by the author. User is responsible for all copyright compliance.</p>"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.du.edu/etd/1795","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Denis Dumas","Peter Organisciak","Garrett Roberts","Jesse Owen"]},{"key":"dc:creator","label":"Author","values":["Maio, Shannon Marie"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2021-02-24T08:00:00Z"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.A."]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Divergent thinking","Elaboration","Originality","Reliability","Text-mining model","Psychology","Statistical Methodology","Statistics and Probability"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["<p>Copyright is held by the author. 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Here, a partial correlation analysis, in conjunction with text-mining and psychometric modeling, is conducted to test the degree to which the reliability of Originality scores produced via a freely-available text-mining system is dependent on the variance explained by Elaboration. Findings reveal that, when modern methodological recommendations for text-mining Originality scoring are applied, the reliability of Originality scores estimated by the GloVe 840B text-mining system is not meaningfully confounded by Elaboration. I conclude that, even when the variance attributed to Elaboration is partialled out, this method is capable of providing reliable Originality scores.</p>"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Is the Reliability of Objective Originality Scores Confounded by Elaboration?"]}]}],"canonical_facts":{"dc:contributor":["Denis Dumas","Peter Organisciak","Garrett Roberts","Jesse Owen"],"dc:creator":["Maio, Shannon Marie"],"dc:date.available":["2021-02-24T08:00:00Z"],"dc:description.abstract":["<p>The increased use of text-mining models as a scoring mechanism for divergent thinking (DT) tasks has sparked concerns about the ways in which automated Originality scores may be influenced by other dimensions of DT, especially Elaboration. The debate centers around the question of whether too much variance in automated Originality scores is accounted for by the number of words a participant uses in a response (i.e., Elaboration), and, thus, how the influence of Elaboration can affect the reliability of Originality scores. Here, a partial correlation analysis, in conjunction with text-mining and psychometric modeling, is conducted to test the degree to which the reliability of Originality scores produced via a freely-available text-mining system is dependent on the variance explained by Elaboration. Findings reveal that, when modern methodological recommendations for text-mining Originality scoring are applied, the reliability of Originality scores estimated by the GloVe 840B text-mining system is not meaningfully confounded by Elaboration. I conclude that, even when the variance attributed to Elaboration is partialled out, this method is capable of providing reliable Originality scores.</p>"],"dc:format":["application/pdf"],"dc:identifier":["https://digitalcommons.du.edu/etd/1795"],"dc:language":["en"],"dc:rights":["<p>Copyright is held by the author. User is responsible for all copyright compliance.</p>"],"dc:subject":["Divergent thinking","Elaboration","Originality","Reliability","Text-mining model","Psychology","Statistical Methodology","Statistics and Probability"],"dc:title":["Is the Reliability of Objective Originality Scores Confounded by Elaboration?"],"thesis:degree_level":["Masters Thesis"],"thesis:degree_name":["M.A."]},"updated_at":"2026-07-24T02:02:19Z"}