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 2025-11-20 — 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，以每日频次对小型随机抽取的美国成年人群体开展调查。受访者需回答一系列形如「<特征标识（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日的汇总调查结果，各字段说明如下： - 特征标识（signifier）：用于描述个体状态的单词、短语或表情符号 - 是计数（yes_count）：全时段汇总后，选择「是」的受访者总人数 - 否计数（no_count）：全时段汇总后，选择「否」的受访者总人数 - 每万人患病率（prevalence_per_10k）：每10000名美国成年人中预计会选择「是」的受访者人数，计算方式为 yes_count / (yes_count + no_count) × 10000 - 最早观测日期（earliest_obs_date）：该特征标识首次展示给受访者的日期。特征标识从长列表中随机抽取生成；研究过程中会新增、删除部分特征标识，同时调整各标识的抽样优先级。 - 最新观测日期（latest_obs_date）：该特征标识最后一次展示给受访者的日期，距当前时间最近。 本数据集版本创建于2025年11月20日，包含累计汇总的调查数据。