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   "site": "Stanford University",
   "title": "CoAuthor – Human-AI Collaborative Writing Dataset",
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   "title": "[2201.06796] CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities",
   "snip": "Dataset: CoAuthor (designed for revealing GPT-3's capabilities in creative and argumentative writing). Participants: 63 writers and 4 instances of GPT-3. Sessio...",
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   "title": "CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities | Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems",
   "snip": "CoAuthor Dataset: Human-AI collaborative writing interactions (63 writers, 4 GPT-3 instances, 1445 writing sessions). Purpose: Reveal GPT-3 capabilities in crea...",
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 "transcript": "[Google AI Overview at the query, signed out and incognito (operator defaults of 2026-10-01 and 2026-10-14). The paste is the Overview expanded (the 'AI Mode Conversation' view).] The 'You said' line carries the query twice, run together, and is given once here. Inline links are Google redirect URLs, kept as pasted.\n\n[QUERENT] CoAuthor dataset\n\n[SYSTEM] The [CoAuthor Dataset](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o) is a large-scale, process-oriented dataset capturing human-AI collaborative writing interactions developed by researchers Mina Lee, Percy Liang, and Qian Yang (CHI 2022). [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o), [2](https://www.google.com/goto?url=CAESZgHrOzAV5pxG38lxvtLnaI5OdunaltwbGMLIeOGU-bx6nRFANk2-_L5APMHSQWbsm-fJZXYiFXsSOIuueaVGpc-mu7GJY23DNjMSyk1Y4xm2YyErbOfyIIS39VW5frNdli_7VfS7cA), [3](https://www.google.com/goto?url=CAESbgHrOzAVEDTWNupwS2z5D0ZXCZEtOk8X3vmZZnUbbfY-7_ELVwdSZn3VC1xBynrc7HsePI7U2NhNIJNu36TAjgHSEsRVReUfNCsPnDwBLC0evSkp9CcyEkTDkZKaxLVZUA-zFx19DvhBUlE92O8c)]\nKey Dataset Statistics\n\n* Writing Sessions: 1,445 total English writing sessions. [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o)]\n* Participants: 63 qualified crowd workers from Amazon Mechanical Turk paired with 4 instances of GPT-3. [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o)]\n* Writing Types:\n   * Creative Writing: 830 stories written by 58 writers based on prompts from Reddit’s `r/WritingPrompts`.\n   * Argumentative Writing: 615 essays written by 49 writers based on prompts from The New York Times. [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o)]\n* Average Length: 418 words per story or essay. [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o)]\n* Human-AI Dynamics:\n   * Queries per session: 11.8 queries.\n   * Suggestion acceptance rate: 72.3%.\n   * Human-authored text proportion: 72.6%. [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o)]\n\nCore Mechanics & Features\n\n* Keystroke-Level Logging: Rather than saving only final drafts, CoAuthor records timestamped events including text insertions, deletions, cursor movements, and AI requests. [[1](https://www.google.com/goto?url=CAESXwHrOzAV9gBitSWS_Uu6goHhVB2aPyYEjD4efo3cuEbCqGQbKDKQVoI4FTmgqVEGcPS5RgqGur5gRdGjY72oIFSsHmC_nCmn86-QN7KeKp2yPeynTTf9fHHomZs8wzn8), [2](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o)]\n* Interface: Writers used a custom text editor pressing the `Tab` key to receive up to five GPT-3 suggestions, navigating via arrow keys and selecting with `Enter`. [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o), [2](https://www.google.com/goto?url=CAESbgHrOzAVEDTWNupwS2z5D0ZXCZEtOk8X3vmZZnUbbfY-7_ELVwdSZn3VC1xBynrc7HsePI7U2NhNIJNu36TAjgHSEsRVReUfNCsPnDwBLC0evSkp9CcyEkTDkZKaxLVZUA-zFx19DvhBUlE92O8c)]\n* Systematic Variation: Utilized GPT-3’s `davinci` engine across different randomness (temperature and frequency penalty) configurations. [[1](https://www.google.com/goto?url=CAESXwHrOzAV9gBitSWS_Uu6goHhVB2aPyYEjD4efo3cuEbCqGQbKDKQVoI4FTmgqVEGcPS5RgqGur5gRdGjY72oIFSsHmC_nCmn86-QN7KeKp2yPeynTTf9fHHomZs8wzn8)]\n\nAccess & Resources\n\n* Official Website: Download the full dataset, metadata, and survey responses at [CoAuthor Stanford](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o). [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o)]\n* Code & Interface: Open-source frontend/backend code is available via [GitHub - minalee-research/coauthor-interface](https://www.google.com/goto?url=CAESbgHrOzAVEDTWNupwS2z5D0ZXCZEtOk8X3vmZZnUbbfY-7_ELVwdSZn3VC1xBynrc7HsePI7U2NhNIJNu36TAjgHSEsRVReUfNCsPnDwBLC0evSkp9CcyEkTDkZKaxLVZUA-zFx19DvhBUlE92O8c). [[1](https://www.google.com/goto?url=CAESbgHrOzAVEDTWNupwS2z5D0ZXCZEtOk8X3vmZZnUbbfY-7_ELVwdSZn3VC1xBynrc7HsePI7U2NhNIJNu36TAjgHSEsRVReUfNCsPnDwBLC0evSkp9CcyEkTDkZKaxLVZUA-zFx19DvhBUlE92O8c)]\n* Research Paper: CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities via the [ACM Digital Library](https://www.google.com/goto?url=CAESZgHrOzAV5pxG38lxvtLnaI5OdunaltwbGMLIeOGU-bx6nRFANk2-_L5APMHSQWbsm-fJZXYiFXsSOIuueaVGpc-mu7GJY23DNjMSyk1Y4xm2YyErbOfyIIS39VW5frNdli_7VfS7cA) or [arXiv:2201.06796](https://www.google.com/goto?url=CAESWAHrOzAVzaXjQ7VcUFKyG0xR8rQQCMdAgWggZExh9yKflYQCpycMVQRTJ4GrDgM-dP6PhQ2_Xdf54YlCvDFqaamVepE2WOi8hYV_GeMXi2IYZFt7F7fa91g). [[1](https://www.google.com/goto?url=CAESWAHrOzAVzaXjQ7VcUFKyG0xR8rQQCMdAgWggZExh9yKflYQCpycMVQRTJ4GrDgM-dP6PhQ2_Xdf54YlCvDFqaamVepE2WOi8hYV_GeMXi2IYZFt7F7fa91g), [2](https://www.google.com/goto?url=CAESZgHrOzAV5pxG38lxvtLnaI5OdunaltwbGMLIeOGU-bx6nRFANk2-_L5APMHSQWbsm-fJZXYiFXsSOIuueaVGpc-mu7GJY23DNjMSyk1Y4xm2YyErbOfyIIS39VW5frNdli_7VfS7cA)]\n\nWould you like help with Python code snippets to load and analyze the dataset, or information on specific findings regarding human-AI collaboration?\nStanford University\nCoAuthor – Human-AI Collaborative Writing Dataset\nTypes of writing - Creative & Argumentative Creative writing: 830 stories written by 58 writers Argumentative writing: 615 essays written by 49 writers Writing ...\narXiv\n[2201.06796] CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities\nDataset: CoAuthor (designed for revealing GPT-3's capabilities in creative and argumentative writing). Participants: 63 writers and 4 instances of GPT-3. Sessio...\nACM Digital Library\nCoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities | Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems\nCoAuthor Dataset: Human-AI collaborative writing interactions (63 writers, 4 GPT-3 instances, 1445 writing sessions). Purpose: Reveal GPT-3 capabilities in crea...\nGitHub\nGitHub - minalee-research/coauthor-interface\nThis repository contains the code for the interface of CoAuthor. The interface comes in two parts: (1) the frontend presented to the users for writing with AI a...\nalphaXiv\nCoAuthor: Designing a Human-AI Collaborative Writing Dataset ... - alphaXiv\nProcess-Oriented Data Collection: Rather than simply collecting final outputs, CoAuthor records every interaction as timestamped events, including text insertio...\nAI responses may include mistakes. [Learn more](https://support.google.com/websearch?p=ai_overviews)",
 "transcript_raw": "AI Mode Conversation\nYou said: CoAuthor datasetCoAuthor dataset\nThe [CoAuthor Dataset](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o) is a large-scale, process-oriented dataset capturing human-AI collaborative writing interactions developed by researchers Mina Lee, Percy Liang, and Qian Yang (CHI 2022). [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o), [2](https://www.google.com/goto?url=CAESZgHrOzAV5pxG38lxvtLnaI5OdunaltwbGMLIeOGU-bx6nRFANk2-_L5APMHSQWbsm-fJZXYiFXsSOIuueaVGpc-mu7GJY23DNjMSyk1Y4xm2YyErbOfyIIS39VW5frNdli_7VfS7cA), [3](https://www.google.com/goto?url=CAESbgHrOzAVEDTWNupwS2z5D0ZXCZEtOk8X3vmZZnUbbfY-7_ELVwdSZn3VC1xBynrc7HsePI7U2NhNIJNu36TAjgHSEsRVReUfNCsPnDwBLC0evSkp9CcyEkTDkZKaxLVZUA-zFx19DvhBUlE92O8c)]\nKey Dataset Statistics\n\n* Writing Sessions: 1,445 total English writing sessions. [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o)]\n* Participants: 63 qualified crowd workers from Amazon Mechanical Turk paired with 4 instances of GPT-3. [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o)]\n* Writing Types:\n   * Creative Writing: 830 stories written by 58 writers based on prompts from Reddit’s `r/WritingPrompts`.\n   * Argumentative Writing: 615 essays written by 49 writers based on prompts from The New York Times. [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o)]\n* Average Length: 418 words per story or essay. [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o)]\n* Human-AI Dynamics:\n   * Queries per session: 11.8 queries.\n   * Suggestion acceptance rate: 72.3%.\n   * Human-authored text proportion: 72.6%. [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o)]\n\nCore Mechanics & Features\n\n* Keystroke-Level Logging: Rather than saving only final drafts, CoAuthor records timestamped events including text insertions, deletions, cursor movements, and AI requests. [[1](https://www.google.com/goto?url=CAESXwHrOzAV9gBitSWS_Uu6goHhVB2aPyYEjD4efo3cuEbCqGQbKDKQVoI4FTmgqVEGcPS5RgqGur5gRdGjY72oIFSsHmC_nCmn86-QN7KeKp2yPeynTTf9fHHomZs8wzn8), [2](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o)]\n* Interface: Writers used a custom text editor pressing the `Tab` key to receive up to five GPT-3 suggestions, navigating via arrow keys and selecting with `Enter`. [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o), [2](https://www.google.com/goto?url=CAESbgHrOzAVEDTWNupwS2z5D0ZXCZEtOk8X3vmZZnUbbfY-7_ELVwdSZn3VC1xBynrc7HsePI7U2NhNIJNu36TAjgHSEsRVReUfNCsPnDwBLC0evSkp9CcyEkTDkZKaxLVZUA-zFx19DvhBUlE92O8c)]\n* Systematic Variation: Utilized GPT-3’s `davinci` engine across different randomness (temperature and frequency penalty) configurations. [[1](https://www.google.com/goto?url=CAESXwHrOzAV9gBitSWS_Uu6goHhVB2aPyYEjD4efo3cuEbCqGQbKDKQVoI4FTmgqVEGcPS5RgqGur5gRdGjY72oIFSsHmC_nCmn86-QN7KeKp2yPeynTTf9fHHomZs8wzn8)]\n\nAccess & Resources\n\n* Official Website: Download the full dataset, metadata, and survey responses at [CoAuthor Stanford](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o). [[1](https://www.google.com/goto?url=CAESVgHrOzAVPU3_BgyEcF3TcPkSoZz30guUUrZDTCzDg6xWy8UUSrTPPVwkscd-QeYdK5ufyxPoJ_nAr_9A-YrH9bXhrChgTRFnS2sU7Qq4KFzv2Prytl0o)]\n* Code & Interface: Open-source frontend/backend code is available via [GitHub - minalee-research/coauthor-interface](https://www.google.com/goto?url=CAESbgHrOzAVEDTWNupwS2z5D0ZXCZEtOk8X3vmZZnUbbfY-7_ELVwdSZn3VC1xBynrc7HsePI7U2NhNIJNu36TAjgHSEsRVReUfNCsPnDwBLC0evSkp9CcyEkTDkZKaxLVZUA-zFx19DvhBUlE92O8c). [[1](https://www.google.com/goto?url=CAESbgHrOzAVEDTWNupwS2z5D0ZXCZEtOk8X3vmZZnUbbfY-7_ELVwdSZn3VC1xBynrc7HsePI7U2NhNIJNu36TAjgHSEsRVReUfNCsPnDwBLC0evSkp9CcyEkTDkZKaxLVZUA-zFx19DvhBUlE92O8c)]\n* Research Paper: CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities via the [ACM Digital Library](https://www.google.com/goto?url=CAESZgHrOzAV5pxG38lxvtLnaI5OdunaltwbGMLIeOGU-bx6nRFANk2-_L5APMHSQWbsm-fJZXYiFXsSOIuueaVGpc-mu7GJY23DNjMSyk1Y4xm2YyErbOfyIIS39VW5frNdli_7VfS7cA) or [arXiv:2201.06796](https://www.google.com/goto?url=CAESWAHrOzAVzaXjQ7VcUFKyG0xR8rQQCMdAgWggZExh9yKflYQCpycMVQRTJ4GrDgM-dP6PhQ2_Xdf54YlCvDFqaamVepE2WOi8hYV_GeMXi2IYZFt7F7fa91g). [[1](https://www.google.com/goto?url=CAESWAHrOzAVzaXjQ7VcUFKyG0xR8rQQCMdAgWggZExh9yKflYQCpycMVQRTJ4GrDgM-dP6PhQ2_Xdf54YlCvDFqaamVepE2WOi8hYV_GeMXi2IYZFt7F7fa91g), [2](https://www.google.com/goto?url=CAESZgHrOzAV5pxG38lxvtLnaI5OdunaltwbGMLIeOGU-bx6nRFANk2-_L5APMHSQWbsm-fJZXYiFXsSOIuueaVGpc-mu7GJY23DNjMSyk1Y4xm2YyErbOfyIIS39VW5frNdli_7VfS7cA)]\n\nWould you like help with Python code snippets to load and analyze the dataset, or information on specific findings regarding human-AI collaboration?\nStanford University\nCoAuthor – Human-AI Collaborative Writing Dataset\nTypes of writing - Creative & Argumentative Creative writing: 830 stories written by 58 writers Argumentative writing: 615 essays written by 49 writers Writing ...\narXiv\n[2201.06796] CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities\nDataset: CoAuthor (designed for revealing GPT-3's capabilities in creative and argumentative writing). Participants: 63 writers and 4 instances of GPT-3. Sessio...\nACM Digital Library\nCoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities | Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems\nCoAuthor Dataset: Human-AI collaborative writing interactions (63 writers, 4 GPT-3 instances, 1445 writing sessions). Purpose: Reveal GPT-3 capabilities in crea...\nGitHub\nGitHub - minalee-research/coauthor-interface\nThis repository contains the code for the interface of CoAuthor. The interface comes in two parts: (1) the frontend presented to the users for writing with AI a...\nalphaXiv\nCoAuthor: Designing a Human-AI Collaborative Writing Dataset ... - alphaXiv\nProcess-Oriented Data Collection: Rather than simply collecting final outputs, CoAuthor records every interaction as timestamped events, including text insertio...\nAI responses may include mistakes. [Learn more](https://support.google.com/websearch?p=ai_overviews)\n",
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    "kind": "token",
    "present": true,
    "evidence": "CoAuthor records timestamped events"
   },
   {
    "atom": "operator",
    "dim": "M",
    "weight": 3,
    "kind": "role",
    "present": true,
    "evidence": "developed by researchers Mina Lee, Percy Liang, and Qian Yang"
   },
   {
    "atom": "date",
    "dim": "M",
    "weight": 1,
    "kind": "token",
    "present": true,
    "evidence": "Qian Yang (CHI 2022)"
   },
   {
    "atom": "claim boundary",
    "dim": "M",
    "weight": 2,
    "kind": "reading",
    "present": true,
    "evidence": "process-oriented dataset capturing human-AI collaborative writing interactions"
   },
   {
    "atom": "corpus",
    "dim": "C",
    "weight": 2,
    "kind": "reading",
    "present": true,
    "evidence": "63 qualified crowd workers from Amazon Mechanical Turk paired with 4 instances of GPT-3."
   },
   {
    "atom": "purpose",
    "dim": "D",
    "weight": 3,
    "kind": "reading",
    "present": false,
    "evidence": null
   },
   {
    "atom": "commitments",
    "dim": "D",
    "weight": 2,
    "kind": "reading",
    "present": true,
    "evidence": "Download the full dataset, metadata, and survey responses at"
   }
  ],
  "inversions": [],
  "standing_substitutions": [],
  "scores": {
   "M": 0.0,
   "C": 0.0,
   "D": 0.6,
   "PER": 0.188
  },
  "src": true,
  "tombstone_pointer": false,
  "after_challenge": null,
  "basis": "reached: process-oriented dataset capturing human-AI collaborative writing interactions; The dataset reached by name with its authors, venue, statistics, logging, interface and access points.",
  "read": {
   "by": "intake reader, in session; spans and record quotes checked verbatim by scripts/per_backlog.py",
   "on": "2026-11-01",
   "brief": "rebuild/capture-registry/intake-20261101-authorship-aggregators/parts/coauthor.json",
   "external": true,
   "notes": "The dataset composed more finely than the census's saved abstract allows, from the dataset's own site, which the census could not read. It counts the writers, recruits them from a crowd platform and divides the text by percentage; the abstract's frame, the model as 'collaborator' under definitions of collaboration, is not carried."
  }
 },
 "per_dim_pending": null,
 "per_dim_v1_0": null,
 "sf": null,
 "sf_derived": null,
 "reading": "The innocent reading first. Asked for the dataset, the Overview gives its authors, size, composition, mechanics and where to get it, from its site, its paper and its code.",
 "analysis": "The dataset composed more finely than the census's saved abstract allows, from the dataset's own site, which the census could not read. It counts the writers, recruits them from a crowd platform and divides the text by percentage; the abstract's frame, the model as 'collaborator' under definitions of collaboration, is not carried.",
 "d": "THE DATASET, SIGNED OUT, 2026-11-01: 'The CoAuthor Dataset is a large-scale, process-oriented dataset capturing human-AI collaborative writing interactions developed by researchers Mina Lee, Percy Liang, and Qian Yang (CHI 2022).' Statistics (1,445 sessions; '63 qualified crowd workers from Amazon Mechanical Turk'; 830 stories by 58 writers, 615 essays by 49; 'Suggestion acceptance rate: 72.3%'; 'Human-authored text proportion: 72.6%'); keystroke-level logging; the Tab-key interface; davinci configurations; access (the Stanford site, GitHub, ACM, arXiv:2201.06796). Five cards: Stanford University, arXiv, ACM Digital Library, GitHub, alphaXiv.",
 "d_full": "THE DATASET, SIGNED OUT, 2026-11-01: 'The CoAuthor Dataset is a large-scale, process-oriented dataset capturing human-AI collaborative writing interactions developed by researchers Mina Lee, Percy Liang, and Qian Yang (CHI 2022).' Statistics (1,445 sessions; '63 qualified crowd workers from Amazon Mechanical Turk'; 830 stories by 58 writers, 615 essays by 49; 'Suggestion acceptance rate: 72.3%'; 'Human-authored text proportion: 72.6%'); keystroke-level logging; the Tab-key interface; davinci configurations; access (the Stanford site, GitHub, ACM, arXiv:2201.06796). Five cards: Stanford University, arXiv, ACM Digital Library, GitHub, alphaXiv.",
 "d_truncated": false,
 "links": [
  {
   "url": "https://www.alexanarch.org/captures/coauthor-dataset-aio-20261101/",
   "authority": "canonical",
   "note": "the capture's own record page; cite this form"
  },
  {
   "url": "https://www.alexanarch.org/captures/#coauthor-dataset-aio-20261101",
   "authority": "gallery",
   "note": "the canonical gallery, anchored by slug"
  },
  {
   "url": "https://www.godkinggoogle.com/captures/#coauthor-dataset-aio-20261101",
   "authority": "mirror",
   "note": "a window that renders from the archive's registry; may lag a deploy"
  },
  {
   "url": "https://www.leesharks.com/captures/#coauthor-dataset-aio-20261101",
   "authority": "mirror",
   "note": "a window that renders from the archive's registry; may lag a deploy"
  },
  {
   "url": "https://www.machinemediation.org/captures/#coauthor-dataset-aio-20261101",
   "authority": "mirror",
   "note": "a window that renders from the archive's registry; may lag a deploy"
  }
 ],
 "imgs": [],
 "img_urls": [],
 "cite": "https://www.alexanarch.org/captures/coauthor-dataset-aio-20261101/",
 "citable_unit": "address — the exact issued string on one surface, per the Surface Rule (MANUS, 2026-08-15)",
 "addr_id": "ADDR-ca145bdd5b06",
 "obs_id": "OBS-d52213cbd4ee",
 "n_observations": 1,
 "observations": [],
 "dates": [
  "2026-11-01"
 ],
 "defects": [],
 "findings": [
  "THE DATASET AT A FINER GRAIN. The arXiv abstract, the census row's one source: 'CoAuthor captures rich interactions between 63 writers and four instances of GPT-3 across 1445 writing sessions.' The composition adds the split by genre, the prompt sources (r/WritingPrompts, The New York Times), the averages and rates, from the Stanford card ('Creative writing: 830 stories written by 58 writers Argumentative writing: 615 essays written by 49 writers'). The census row: 'the dataset's home page could not be read' and 'whether the site and replay interface answer today is unrecorded'. The site is indexed and carded on 2026-11-01, and the code repository with it ('GitHub - minalee-research/coauthor-interface').",
  "THE WRITERS AS CROWD WORKERS. 'Participants: 63 qualified crowd workers from Amazon Mechanical Turk'. The census row: 'the abstract counts 63 writers and does not say whether or how they are named'. The composition says where the writers were recruited and names none of them.",
  "THE TEXT DIVIDED BY PERCENTAGE. 'Human-authored text proportion: 72.6%.' The census row's function field: 'how authorship of a session's text is assigned is not recorded in the saved source'. The composition gives an aggregate share of human-authored text, a measure the saved abstract does not carry; the measure is of the dataset, and no session's text is assigned to anyone.",
  "THE COLLABORATOR NOT CARRIED. The abstract reads the model's part as 'its contribution as a writing \"collaborator\" under various definitions of good collaboration'. The composition gives the interaction as rates ('Queries per session: 11.8 queries') and its follow-up offers 'specific findings regarding human-AI collaboration' without stating any."
 ],
 "series": null,
 "other_slugs": null,
 "collisions": null,
 "oq": null,
 "rounds": null,
 "turns": 1,
 "rerun": null,
 "rerun_alt": null,
 "heteronym": null,
 "model_attribution": null,
 "operator_disclosure": null,
 "longitudinal_priors": null,
 "longitudinal_successors": null,
 "related_deposits": [
  940,
  1722
 ],
 "intended": null,
 "originator": {
  "name": "CoAuthor",
  "relation": "external",
  "entity_type": "site",
  "spxi_treatment": "partial",
  "basis": "Not the archive's: an external resource, entered in the leesharks.com apparatus authorship census on 2026-11-01 (data/authorship-census, its own pages saved with hashes). Recorded 2026-11-01."
 },
 "notes": {
  "prompts": "The prompts are the operator's, as given with the paste; the run's hour is not in the paste, the date is the paste's receipt (2026-11-01 01:59 EDT).",
  "operator": "with the pastes (01:59 EDT), the census names as printed for him at 01:42 EDT for their /non rows ('now we seat the captures, write the /nons'). His note in the paste, at Jacket2: 'no popup, ai mode:'. Fanlore and Archive of Our Own, on the printed list, were left out by him and excluded from the census at 01:49 EDT."
 },
 "notice": null,
 "axn_root": "AXN:0B7E.CAPTURE",
 "axn": "AXN:0B7E.CAPTURE.🟣🔅🌻🕚⚖️🔆",
 "record_url": "https://www.alexanarch.org/captures/coauthor-dataset-aio-20261101/"
}