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 2026-01-13 — cumulative data.个体自述为X的比例是多少？ 本研究于2025年7月8日启动，以每日调研的频次对少量美国成年随机样本进行调查。受访者需回答大量形如「<signifier>（signifier）是否符合你今日的状态？」的问题。 本仓库中的ipseity-daily-aggregated.csv文件收录了截至2025年7月28日的聚合调研结果，各字段说明如下： - signifier（标识词）：单词、短语或表情符号 - yes_count（肯定应答数）：全时间维度下选择肯定回答的受访者总数量 - no_count（否定应答数）：全时间维度下选择否定回答的受访者总数量 - prevalence_per_10k（每万人流行率估算值）：针对每10000名美国成年人的肯定应答预估占比。即若调研10000名美国成年人，预计会有多少受访者对该标识词给出肯定回答。该指标计算公式为：yes_count / (yes_count + no_count) × 10000。 - earliest_obs_date（最早观测日期）：该特定标识词首次向受访者展示的日期。标识词从长列表中通过随机抽样选取；有时会新增标识词、删除旧有标识词，或调整标识词在抽样中的优先级。 - latest_obs_date（最新观测日期）：该标识词最近一次向受访者展示的、距离当前时间最近的日期。 本数据集版本创建于2026年1月13日，包含累计调研数据。