{"id":{"repo_id":"uwo","oai_identifier":"oai:uwo.scholaris.ca:20.500.14721/39063"},"canonical_url":"https://search.dev.ndltd.org/etd/uwo/oai:uwo.scholaris.ca:20.500.14721/39063","repository":{"repo_id":"uwo","name":"Western University","base_url":"https://uwo.scholaris.ca/server/oai/request"},"display":{"title":"Explicit Feature Relation and Implicit Feature Correlation Knowledge in Semantic Memory","abstract":"Existing literature suggests that failures to find influences of statistically-based or theorybased knowledge in learning feature co-occurrences are attributable to incongruence between task type (speeded versus untimed) and knowledge type (statistically-based versus theory-based), though these knowledge types influence congruent tasks (McRae, de Sa & Seidenberg, 1997; Ahn, Marsh, Luhmann & Lee, 2002). I argue that influence of both knowledge types should be found in tasks that directly tap feature co-occurrence knowledge, allowing meaningful contrasts of their influences. Detailed descriptions of causal theories were collected using interviews. Regression analyses using theory statistics and shared variance between features were used to compare the relative influences of the two knowledge types in untimed relatedness ratings and speeded relatedness decisions for 65 feature pairs that span a range of correlational strength. Both knowledge types influenced both tasks. It is concluded that both implicitly and explicitly correlated feature pairs influence conceptual computations.","abstract_html":"Existing literature suggests that failures to find influences of statistically-based or theorybased knowledge in learning feature co-occurrences are attributable to incongruence between task type (speeded versus untimed) and knowledge type (statistically-based versus theory-based), though these knowledge types influence congruent tasks (McRae, de Sa & Seidenberg, 1997; Ahn, Marsh, Luhmann & Lee, 2002). I argue that influence of both knowledge types should be found in tasks that directly tap feature co-occurrence knowledge, allowing meaningful contrasts of their influences. Detailed descriptions of causal theories were collected using interviews. Regression analyses using theory statistics and shared variance between features were used to compare the relative influences of the two knowledge types in untimed relatedness ratings and speeded relatedness decisions for 65 feature pairs that span a range of correlational strength. Both knowledge types influenced both tasks. It is concluded that both implicitly and explicitly correlated feature pairs influence conceptual computations.","abstract_has_math":false,"creators":["McNorgan, Christopher P."],"institution":"The University of Western Ontario","degree_name":"Master of Arts","degree_level":null,"degree_discipline":"Psychology","degree_department":null,"school":null,"contributors":[],"advisors":["McRae, Ken"],"committee_chairs":[],"committee_members":[],"year":2004,"date_issued":"2004","date_published":"2004","updated_at":"2026-07-27T21:56:18Z","subjects":["correlated features","causal theories","speeded tasks","untimed tasks","knowledge types."],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/20.500.14721/39063","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["McRae, Ken"]},{"key":"dc:creator","label":"Author","values":["McNorgan, Christopher P."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-11-14T19:17:19Z"]},{"key":"dc:date.issued","label":"Date","values":["2004"]},{"key":"dc:publisher","label":"Institution","values":["The University of Western Ontario"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Psychology"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Arts"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The University of Western Ontario"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["correlated features","causal theories","speeded tasks","untimed tasks","knowledge types."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/20.500.14721/39063"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Existing literature suggests that failures to find influences of statistically-based or theorybased knowledge in learning feature co-occurrences are attributable to incongruence between task type (speeded versus untimed) and knowledge type (statistically-based versus theory-based), though these knowledge types influence congruent tasks (McRae, de Sa & Seidenberg, 1997; Ahn, Marsh, Luhmann & Lee, 2002). I argue that influence of both knowledge types should be found in tasks that directly tap feature co-occurrence knowledge, allowing meaningful contrasts of their influences. Detailed descriptions of causal theories were collected using interviews. Regression analyses using theory statistics and shared variance between features were used to compare the relative influences of the two knowledge types in untimed relatedness ratings and speeded relatedness decisions for 65 feature pairs that span a range of correlational strength. Both knowledge types influenced both tasks. It is concluded that both implicitly and explicitly correlated feature pairs influence conceptual computations."]},{"key":"dc:title","label":"Title","values":["Explicit Feature Relation and Implicit Feature Correlation Knowledge in Semantic Memory"]}]}],"canonical_facts":{"dc:contributor.advisor":["McRae, Ken"],"dc:creator":["McNorgan, Christopher P."],"dc:date.accessioned":["2025-11-14T19:17:19Z"],"dc:date.issued":["2004"],"dc:description.abstract":["Existing literature suggests that failures to find influences of statistically-based or theorybased knowledge in learning feature co-occurrences are attributable to incongruence between task type (speeded versus untimed) and knowledge type (statistically-based versus theory-based), though these knowledge types influence congruent tasks (McRae, de Sa & Seidenberg, 1997; Ahn, Marsh, Luhmann & Lee, 2002). I argue that influence of both knowledge types should be found in tasks that directly tap feature co-occurrence knowledge, allowing meaningful contrasts of their influences. Detailed descriptions of causal theories were collected using interviews. Regression analyses using theory statistics and shared variance between features were used to compare the relative influences of the two knowledge types in untimed relatedness ratings and speeded relatedness decisions for 65 feature pairs that span a range of correlational strength. Both knowledge types influenced both tasks. It is concluded that both implicitly and explicitly correlated feature pairs influence conceptual computations."],"dc:identifier.uri":["https://hdl.handle.net/20.500.14721/39063"],"dc:language.iso":["en"],"dc:publisher":["The University of Western Ontario"],"dc:subject":["correlated features","causal theories","speeded tasks","untimed tasks","knowledge types."],"dc:title":["Explicit Feature Relation and Implicit Feature Correlation Knowledge in Semantic Memory"],"dc:type":["Thesis"],"thesis:degree_discipline":["Psychology"],"thesis:degree_name":["Master of Arts"],"thesis:institution_name":["The University of Western Ontario"]},"updated_at":"2026-07-27T21:56:18Z"}