[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-82143-en":3,"doc-seo-82143-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},82143,1099514067438,"River Wang","https://ap-avatar.wpscdn.com/avatar/100002539ee87300030?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780474512215547542",8,"Research & Report","Living Inside the Black Box: Behavioral Probing and Adaptation in Mandatory Wearable Sensing","Wearable sensing systems in high-stakes institutional settings translate behavioral data into consequential compliance judgments, while wearers often cannot access how decisions are made. A qualitative study of 24 participants who experienced mandatory electronic monitoring in China’s community corrections system finds that individuals develop “sensor literacy under constraint.” This risk-oriented knowledge emerges through uncertainty handling, behavioral probing, and adaptation. Two orientations appear across rule domains, shaping flexibility or contraction of movement and discretionary activity.","Living Inside the Black Box: Behavioral Probing and Adaptation  \nin Mandatory Wearable Sensing  \nYibo Meng∗ [yim4007@med.cornell.edu](yim4007@med.cornell.edu)[ ](yim4007@med.cornell.edu)Weill Cornell Medicine, Cornell University New York, New York, USA  \nBingyi Liu  \nUniversity of Michigan Ann Arbor, Michigan, USA [bingyi@umich.edu](bingyi@umich.edu)  \nRuiqi Chen  \nUniversity of Washington Seattle, Washington, USA [ruiqich@uw.edu](ruiqich@uw.edu)  \nXiaolan Ding  \nNorth China University of Science and Technology Tangshan, China  \nShuai Ma Aalto University Helsinki, Finland [shuai.ma@aalto.fi](shuai.ma@aalto.fi)  \narXiv :2607 .09009v1 [ cs .HC] 10 Jul 2026  \nAbstract  \nWearable sensing systems in high-stakes institutional contexts translate behavioral data into consequential judgments, yet wearershave little access to how those judgments are made. We present a qualitative study of 24 individuals who experienced mandatory electronic monitoring in China’s community corrections system. We show that participants built what we term sensor literacy under constraint, a practical form of risk-oriented knowledge developed through uncertainty, behavioral probing, and adaptation. We identify two orientations across rule domains. Where participants had mapped system behavior, they sometimes regained limited flexibility. Where uncertainty remained costly, they contracted movement and discretionary activity beyond formal rules. Some former wearers described residual habits of calculation after device removal.  \nWe discuss design implications for making institutional sensing intelligible to wearers, including sensor uncertainty, usable documentation, and evaluation after device wearing.  \nCCS Concepts  \n• Human-centered computing → Empirical studies in ubiquitous and mobile computing; Empirical studies in HCI; Empirical studies in collaborative and social computing.  \nKeywords  \nelectronic monitoring, wearable sensing, sensor literacy, behavioral calibration, algorithmic opacity, design implications  \n1 Introduction  \nWearable sensing systems are increasingly deployed in high-stakes institutional contexts, where sensor data shape consequential decisions about people’s lives [1, 25] . Electronic monitoring (EM) is an extreme instance of this condition. Individuals under community supervision wear GPS ankle devices, smart wristbands, or mobile applications continuously. These systems record location, movement, and behavioral data around the clock. The data are translated into compliance judgments with legal consequences. The interpretive logic behind those judgments remains largely inaccessible to the people wearing the devices.  \nIn the deployment reported by participants, EM centered on location and geofence monitoring, scheduled check-ins, and device status such as battery level and signal availability. Wearers encountered the system mainly through a worn device, a paired application for some participants, and follow-up communication from supervising staff. We do not reconstruct operator-side settings or institutional decision rules. Instead, we analyze what was made legible to wearers and how they acted under those limits.  \nSensor records do not carry fixed meaning. A boundary crossing, signal interruption, or timing deviation may reflect GPS drift, environmental interference, or actual non-compliance [10, 14] . Wearers rarely know how such ambiguities are resolved. They must act not only under observation, but under uncertainty about how their actions will be evaluated [13, 21] .  \nPrior work on EM has focused on compliance outcomes, recidivism, and institutional practices [2] . It has also examined legal risks, false alerts, perceived punitiveness, and accountability around location-based supervision [11, 16, 22] . Research on wearable sensing in ubicomp and HCI has examined fitness trackers, health monitors, and other devices that users choose and can exit [5, 7]. These settings involve low stakes, user control, and voluntary participati","cbCainup9Y8U8vtP","https://ap.wps.com/l/cbCainup9Y8U8vtP","pdf",464943,4,1,7,"English","en",105,"# Abstract\n# CCS Concepts\n# Keywords\n# Introduction\n## Wearable sensing in high-stakes institutional contexts\n## Electronic monitoring as an opaque decision pipeline\n## Prior work and research gap\n## Qualitative study approach\n## Central argument: sensor literacy under constraint","[{\"question\":\"What is the main finding of the study on mandatory wearable sensing?\",\"answer\":\"Participants under mandatory electronic monitoring developed “sensor literacy under constraint,” a form of risk-oriented knowledge. They learned how the system behaved by testing it under uncertainty and institutional consequences.\"},{\"question\":\"How do participants learn when sensor data meanings are ambiguous?\",\"answer\":\"Sensor uncertainty drives experimental probing, such as observing geofence boundaries, delaying check-ins, or monitoring device behavior like battery runtime. Over time, this produces practical orientations about what is tolerated and how actions are evaluated.\"},{\"question\":\"What are the two orientations across rule domains reported in the study?\",\"answer\":\"When participants mapped system behavior, they sometimes regained limited flexibility. When uncertainty remained costly, many contracted movement and discretionary activity beyond formal rules and avoided boundary-adjacent decisions.\"}]",1784178424,18,{"code":4,"msg":31,"data":32},"ok",{"site_id":25,"language":24,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"living-inside-the-black-box-behavioral-probing-and-adaptation-in-mandatory-wearable-sensing","",{"@graph":36,"@context":85},[37,53,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":20},"https://docshare.wps.com/document/living-inside-the-black-box-behavioral-probing-and-adaptation-in-mandatory-wearable-sensing/82143/",{"url":52,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":24,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-20","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the main finding of the study on mandatory wearable sensing?","Question",{"text":75,"@type":76},"Participants under mandatory electronic monitoring developed “sensor literacy under constraint,” a form of risk-oriented knowledge. They learned how the system behaved by testing it under uncertainty and institutional consequences.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How do participants learn when sensor data meanings are ambiguous?",{"text":80,"@type":76},"Sensor uncertainty drives experimental probing, such as observing geofence boundaries, delaying check-ins, or monitoring device behavior like battery runtime. Over time, this produces practical orientations about what is tolerated and how actions are evaluated.",{"name":82,"@type":73,"acceptedAnswer":83},"What are the two orientations across rule domains reported in the study?",{"text":84,"@type":76},"When participants mapped system behavior, they sometimes regained limited flexibility. When uncertainty remained costly, many contracted movement and discretionary activity beyond formal rules and avoided boundary-adjacent decisions.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,119,122,127,130,134],{"id":21,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":20,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":22,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]