{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:UOB56D7MZQIDNDYW2JUHYU52HH","short_pith_number":"pith:UOB56D7M","schema_version":"1.0","canonical_sha256":"a383df0feccc10368f16d2687c53ba39ec96236f1e58b701b47b711803da5c30","source":{"kind":"arxiv","id":"2501.19275","version":4},"attestation_state":"computed","paper":{"title":"From Assistance to Autonomy -- A Researcher Study on the Potential of AI Support for Qualitative Data Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CY","authors_text":"Abraham Mhaidli, Annalina Buckmann, Elisabeth Kirsten, Leona Lassak, Nele Borgert, Steffen Becker","submitted_at":"2025-01-31T16:37:19Z","abstract_excerpt":"The advent of AI technologies, such as Large Language Models, has introduced new possibilities for Qualitative Data Analysis (QDA), offering both opportunities and challenges. To help navigate the responsible integration of AI into QDA, we conducted semi-structured interviews with 15 Human-Computer Interaction (HCI) researchers experienced in QDA. While our participants were open to AI support in their QDA workflows, they expressed concerns about data privacy, autonomy, and the quality of AI outputs. In response, we developed a framework that spans from minimal to high AI involvement, providin"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2501.19275","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2025-01-31T16:37:19Z","cross_cats_sorted":[],"title_canon_sha256":"684a7beb4ae620f0e9b9721493af5216a6ea41b1130a8283068d3f77474dc3bd","abstract_canon_sha256":"ad89e5075df336431111ad5528d73cd5ceff5a0f35240c8eae04aa5a67c94ae5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-23T01:24:14.497739Z","signature_b64":"huHieX5LXLGwqXZSEao0fUBoo1zmD2/X3eQfxe28F/5V1zKmSRHp9+ScJ+p6yp7LJdpHp8gm/YmFbKlNy2ZjBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a383df0feccc10368f16d2687c53ba39ec96236f1e58b701b47b711803da5c30","last_reissued_at":"2026-07-23T01:24:14.496709Z","signature_status":"signed_v1","first_computed_at":"2026-07-23T01:24:14.496709Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"From Assistance to Autonomy -- A Researcher Study on the Potential of AI Support for Qualitative Data Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CY","authors_text":"Abraham Mhaidli, Annalina Buckmann, Elisabeth Kirsten, Leona Lassak, Nele Borgert, Steffen Becker","submitted_at":"2025-01-31T16:37:19Z","abstract_excerpt":"The advent of AI technologies, such as Large Language Models, has introduced new possibilities for Qualitative Data Analysis (QDA), offering both opportunities and challenges. To help navigate the responsible integration of AI into QDA, we conducted semi-structured interviews with 15 Human-Computer Interaction (HCI) researchers experienced in QDA. While our participants were open to AI support in their QDA workflows, they expressed concerns about data privacy, autonomy, and the quality of AI outputs. In response, we developed a framework that spans from minimal to high AI involvement, providin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.19275","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2501.19275/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2501.19275","created_at":"2026-07-23T01:24:14.497188+00:00"},{"alias_kind":"arxiv_version","alias_value":"2501.19275v4","created_at":"2026-07-23T01:24:14.497188+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.19275","created_at":"2026-07-23T01:24:14.497188+00:00"},{"alias_kind":"pith_short_12","alias_value":"UOB56D7MZQID","created_at":"2026-07-23T01:24:14.497188+00:00"},{"alias_kind":"pith_short_16","alias_value":"UOB56D7MZQIDNDYW","created_at":"2026-07-23T01:24:14.497188+00:00"},{"alias_kind":"pith_short_8","alias_value":"UOB56D7M","created_at":"2026-07-23T01:24:14.497188+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2507.05010","citing_title":"Co-DETECT: Collaborative Discovery of Edge Cases in Text Classification","ref_index":22,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/UOB56D7MZQIDNDYW2JUHYU52HH","json":"https://pith.science/pith/UOB56D7MZQIDNDYW2JUHYU52HH.json","graph_json":"https://pith.science/api/pith-number/UOB56D7MZQIDNDYW2JUHYU52HH/graph.json","events_json":"https://pith.science/api/pith-number/UOB56D7MZQIDNDYW2JUHYU52HH/events.json","paper":"https://pith.science/paper/UOB56D7M"},"agent_actions":{"view_html":"https://pith.science/pith/UOB56D7MZQIDNDYW2JUHYU52HH","download_json":"https://pith.science/pith/UOB56D7MZQIDNDYW2JUHYU52HH.json","view_paper":"https://pith.science/paper/UOB56D7M","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2501.19275&json=true","fetch_graph":"https://pith.science/api/pith-number/UOB56D7MZQIDNDYW2JUHYU52HH/graph.json","fetch_events":"https://pith.science/api/pith-number/UOB56D7MZQIDNDYW2JUHYU52HH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UOB56D7MZQIDNDYW2JUHYU52HH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UOB56D7MZQIDNDYW2JUHYU52HH/action/storage_attestation","attest_author":"https://pith.science/pith/UOB56D7MZQIDNDYW2JUHYU52HH/action/author_attestation","sign_citation":"https://pith.science/pith/UOB56D7MZQIDNDYW2JUHYU52HH/action/citation_signature","submit_replication":"https://pith.science/pith/UOB56D7MZQIDNDYW2JUHYU52HH/action/replication_record"}},"created_at":"2026-07-23T01:24:14.497188+00:00","updated_at":"2026-07-23T01:24:14.497188+00:00"}