Ipseity Daily Data

At what rate do individuals say they are X? Begining on 2025-07-08, I surveyed a small random sample of American adults on a daily cadence. They responded to many items of the form: Does <signifier> describe you today? The file ipseity-daily-aggregated.csv in this repository contains the aggregated results through 2025-07-28. The columns are as follows: signifier - a word, phrase or emoji yes_count - the number of respondents who answered yes (aggregated all-time). no_count - the number of respondents who answered no (aggregated all-time). prevalence_per_10k - an estimate of the prevalence per 10,000. If we were to survey 10,000 American adults, how many would we expect to respond yes to this signifier? The number is calculated as yes_count / (yes_count + no_count) * 10,000. earliest_obs_date - this date represents the first time this particular signifier was ever displayed to a respondent. Signifiers are chosen with stochasticity from a long list; new signifiers are sometimes added, old signifiers are sometimes deleted, and a signifier may be moved higher or lower in priority for sampling. latest_obs_date - the date closest to the present date on which signifier was most recently presented to a respondent. Version created on 2026-04-06 — cumulative data.个体自述符合特征X的比例为多少？ 本研究自2025年7月8日起，以每日频次对小型美国成年人随机样本开展调查。受访者需回答大量形如「<标识符（signifier）>是否符合你今日的状态？」的问题。 本仓库中的ipseity-daily-aggregated.csv文件包含截至2025年7月28日的汇总调查结果，各字段说明如下： - 标识符（signifier）：单词、短语或表情符号 - 肯定应答数（yes_count）：累计全时段选择“是”的受访者总人数 - 否定应答数（no_count）：累计全时段选择“否”的受访者总人数 - 万分之一流行率（prevalence_per_10k）：每10000名美国成年人中预计会对该标识符给出肯定应答的人数估算值，计算公式为：yes_count / (yes_count + no_count) × 10000 - 首次观测日期（earliest_obs_date）：该标识符首次向受访者展示的日期。标识符从长列表中随机抽取；研究期间会新增、删除部分标识符，或调整各标识符的抽样优先级 - 末次观测日期（latest_obs_date）：该标识符最近一次向受访者展示的日期，最接近当前时间 本数据集版本创建于2026年4月6日，包含累计调查数据。