{"id":"https://openalex.org/W7162074664","doi":"https://doi.org/10.48550/arxiv.2605.22641","title":"More Context, Larger Models, or Moral Knowledge? A Systematic Study of Schwartz Value Detection in Political Texts","display_name":"More Context, Larger Models, or Moral Knowledge? A Systematic Study of Schwartz Value Detection in Political Texts","publication_year":2026,"publication_date":"2026-05-21","ids":{"openalex":"https://openalex.org/W7162074664","doi":"https://doi.org/10.48550/arxiv.2605.22641"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.22641","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.22641","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.22641","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136736663","display_name":"V\u00edctor Yeste","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yeste, V\u00edctor","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136736760","display_name":"Paolo Rosso","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rosso, Paolo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.296099990606308,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.296099990606308,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.2881999909877777,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.15719999372959137,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.7060999870300293},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.6620000004768372},{"id":"https://openalex.org/keywords/politics","display_name":"Politics","score":0.5185999870300293},{"id":"https://openalex.org/keywords/situated","display_name":"Situated","score":0.5030999779701233},{"id":"https://openalex.org/keywords/truth-value","display_name":"Truth value","score":0.35040000081062317},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.3407000005245209}],"concepts":[{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.7060999870300293},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.6620000004768372},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.5185999870300293},{"id":"https://openalex.org/C132829578","wikidata":"https://www.wikidata.org/wiki/Q581151","display_name":"Situated","level":2,"score":0.5030999779701233},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.49390000104904175},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.46149998903274536},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.4090000092983246},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.3905999958515167},{"id":"https://openalex.org/C46274116","wikidata":"https://www.wikidata.org/wiki/Q185521","display_name":"Truth value","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.3407000005245209},{"id":"https://openalex.org/C3019719930","wikidata":"https://www.wikidata.org/wiki/Q3910099","display_name":"Predictive value","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C102912713","wikidata":"https://www.wikidata.org/wiki/Q3187415","display_name":"Value theory","level":2,"score":0.3343000113964081},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33390000462532043},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3310000002384186},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.32359999418258667},{"id":"https://openalex.org/C76188268","wikidata":"https://www.wikidata.org/wiki/Q1783165","display_name":"Context effect","level":3,"score":0.3231000006198883},{"id":"https://openalex.org/C11693617","wikidata":"https://www.wikidata.org/wiki/Q181839","display_name":"Pragmatics","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.27230000495910645},{"id":"https://openalex.org/C91682802","wikidata":"https://www.wikidata.org/wiki/Q620538","display_name":"Multidimensional scaling","level":2,"score":0.2556000053882599}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.22641","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.22641","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.22641","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.22641","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Detecting":[0],"Schwartz":[1],"values":[2],"in":[3,104],"political":[4],"text":[5],"is":[6,73,100],"difficult":[7],"because":[8],"implicit":[9],"cues":[10],"often":[11],"depend":[12],"on":[13],"surrounding":[14],"arguments":[15],"and":[16,26,43,47,59,112,124,134,142,153,174],"fine-grained":[17],"distinctions":[18],"between":[19],"neighboring":[20],"values.":[21,163],"We":[22],"study":[23],"when":[24],"context":[25,72,78,113,152],"explicit":[27],"moral":[28,53,98],"knowledge":[29,54,99],"help":[30,94,155],"sentence-level":[31],"value":[32],"detection.":[33],"Using":[34],"the":[35,139],"ValuesML/Touch\u00e9":[36],"ValueEval":[37],"format,":[38],"we":[39],"compare":[40],"sentence,":[41],"window,":[42],"full-document":[44,77],"inputs;":[45],"no-RAG":[46],"retrieval-augmented":[48],"settings":[49],"with":[50],"a":[51],"curated":[52],"base;":[55],"supervised":[56,80],"DeBERTa-v3-base/large":[57],"encoders;":[58],"zero-shot":[60,95],"LLMs":[61,129],"from":[62,120,125],"12B":[63,126],"to":[64,122,127],"123B":[65],"parameters.":[66],"The":[67],"results":[68],"show":[69,150],"that":[70,151,167],"more":[71,101],"not":[74,92,131],"uniformly":[75],"better:":[76],"improves":[79],"DeBERTa":[81],"encoders":[82],"by":[83],"3.8-4.8":[84],"macro-F1":[85],"points":[86],"over":[87],"sentence-only":[88],"input,":[89],"but":[90],"does":[91,130],"consistently":[93,102],"LLMs.":[96],"Retrieved":[97],"useful":[103],"matched":[105],"comparisons,":[106],"improving":[107],"each":[108],"tested":[109,140],"model":[110,175],"family":[111,176],"condition":[114],"under":[115],"early":[116,136],"fusion.":[117],"However,":[118],"scaling":[119],"DeBERTa-v3-base":[121],"large":[123],"larger":[128,184],"guarantee":[132],"gains,":[133],"simple":[135],"fusion":[137],"outperforms":[138],"late-fusion":[141],"cross-attention":[143],"RAG":[144],"variants":[145],"for":[146,157],"encoders.":[147],"Per-value":[148],"analyses":[149],"retrieval":[154],"most":[156],"socially":[158],"situated":[159],"or":[160,183],"conceptually":[161],"confusable":[162],"These":[164],"findings":[165],"suggest":[166],"value-sensitive":[168],"NLP":[169],"should":[170],"evaluate":[171],"context,":[172],"knowledge,":[173],"jointly":[177],"rather":[178],"than":[179],"treating":[180],"longer":[181],"inputs":[182],"models":[185],"as":[186],"universal":[187],"improvements.":[188]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-23T00:00:00"}
