标题:随机漫步的傻瓜 [投资理财] 简介: 你的成功可能只是运气的结果,而非能力更高。牙医比摇滚乐手或投机客更富有,因为职业生涯风险低、灾难少。生活充满不确定性,随机事件常带来大起大落。黑天鹅可能让你一夜暴富,也可能瞬间归零。我们却倾向忽视低概率事件的巨大影响。本书揭示随机世界的规律,教我们接受随机性:若小概率事件能带来巨额回报,为何不持续下注?换个思维,对人生的理解将大为增进。 链接: https://pan.quark.cn/s/fd96caffc7f8 🏷标签: #投资理财 👥 群组:@BooksRealm

Channel
书之领域图书馆
@BooksRealm
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
15,009subscribers
+31 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1002045628294 |
|---|---|
| Type | Channel |
| Username | @BooksRealm |
| Description | 在书的海洋翱翔 把时间留给阅读 多种格式的综合书籍资源分享下载频道 |
| Created | Between 1 November 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 21 August 2026 |
| Measurements held | 16 |
| Confirmed unchanged | 1 time, most recently 21 August 2026 |
| On Telegram | t.me/BooksRealm |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 21 Aug 2026, 19:08 | 15,009 | -2 |
| 20 Aug 2026, 16:15 | 15,011 | +1 |
| 19 Aug 2026, 17:58 | 15,010 | +3 |
| 18 Aug 2026, 21:04 | 15,007 | +2 |
| 18 Aug 2026, 00:33 | 15,005 | +4 |
| 16 Aug 2026, 22:19 | 15,001 | +3 |
| 15 Aug 2026, 15:34 | 14,998 | +2 |
| 14 Aug 2026, 01:58 | 14,996 | -1 |
| 12 Aug 2026, 17:44 | 14,997 | -2 |
| 11 Aug 2026, 18:38 | 14,999 | +7 |
| 10 Aug 2026, 16:52 | 14,992 | -1 |
| 9 Aug 2026, 15:21 | 14,993 | +5 |
| 8 Aug 2026, 17:37 | 14,988 | +9 |
| 7 Aug 2026, 17:50 | 14,979 | +1 |
| 7 Aug 2026, 15:30 | 14,978 | no change |
| 7 Aug 2026, 15:26 | 14,978 | first reading |
Engagement
43 posts held, back to 1 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 33 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 2.61%
- avg views ÷ 15,009 subscribers
- Avg views / post
- 392
- 43 posts measured
- Reaction rate
- 0.143%
- reactions ÷ views · ER floor
- Posts in window
- 43
- of 43 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 7 of 43 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 22 August 2026 |
|---|---|
| Posts held | 43 (1 August 2026 – 22 August 2026) |
| Views total | 16,847 |
| Reactions total | 7 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 23 Aug 2026, 00:44 UTC |
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
- Photos
- ≈8,020
- Links
- ≈7,840
Lifetime counters from Telegram’s own channel header, read 23 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Reaction mix
7 reactions across 6 posts, in 2 distinct kinds. The most used accounts for 85.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 6 | 85.7% | |
| 👍 | 1 | 14.3% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 7 of the 43 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 7reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 43 most recent posts we hold, published 1 August 2026 to 22 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Recent posts
标题:收容所:精神病人及其他被收容者的社会情境 [社會科學] 简介: 本书探讨了精神病院等“全控机构”如何通过收缴个人物品、清除社会身份、集体管制等手段瓦解个体自我认同,将人重塑为温顺的“被收容者”。戈夫曼指出,“正常”与“疯癫”的界限由制度建构,机构的核心功能是控制而非治愈。该书为理解权力运作、身份建构及边缘群体处境提供了经典分析框架,并推动了全球精神卫生领域的“去机构化”运动,引发对现代社会如何制造“疯癫”的深刻拷问。 链接: https://pan.quark.cn/s/824c64d046f9 🏷标签: #社會科學 👥 群组:@BooksRealm
标题:收容所:精神病人及其他被收容者的社会情境 [社會科學] 简介: 本书探讨了精神病院等“全控机构”如何通过收缴个人物品、清除社会身份、集体管制等手段瓦解个体自我认同,将人重塑为温顺的“被收容者”。戈夫曼指出,“正常”与“疯癫”的界限由制度建构,机构的核心功能是控制而非治愈。该书为理解权力运作、身份建构及边缘群体处境提供了经典分析框架,并推动了全球精神卫生领域的“去机构化”运动,引发对现代社会如何制造“疯癫”的深刻拷问。 链接: https://pan.quark.cn/s/824c64d046f9 🏷标签: #社會科學 👥 群组:@BooksRealm
标题:求偶智力:性、约会与爱情的心理机制 [心理科學] 简介: 《求偶智力》提出,人类求偶不仅受本能支配,还受一种经长期演化形成的心理能力——求偶智力所影响。它指引调情、伴侣选择、亲密关系建立等行为。本书融合进化心理学、生物学等多学科研究,探讨创造力、人格、幽默、欺骗等因素在求偶中的作用,并解答了为何聪明人在感情中笨拙、好男人是否垫底等有趣问题,揭示了求偶与智力之间的深刻关联。 链接: https://pan.quark.cn/s/648776012b0b 🏷标签: #心理科學 👥 群组:@BooksRealm
标题:普京正传:权势之王 [文學傳記] 简介: 他是俄罗斯的铁腕总统,从克格勃特工到三任总统、两任总理,被誉为“权势之王”。出身平凡,却以强硬作风复兴俄罗斯大国地位:对内整顿经济、打击寡头、加强军队;对外拓展外交,维护国家利益。他酷爱飞行、柔道,充满神秘魅力,在人民需要时总能站在最前沿。本书全面诠释了一个真实而完整的普京。 链接: https://pan.quark.cn/s/d46cf2c8e7ec 🏷标签: #文學傳記 👥 群组:@BooksRealm
标题:漂亮的失败是另一种成功 [成功勵誌] 简介: 《“漂亮”的失败是另一种成功》是一本激励人们从失败中汲取力量、走向成功的书。书中用大量案例和全新视角,告诉读者如何正视失败、借鉴失败,把失败当作宝贵财富和另一种成功。内容涵盖正视失败、享受过程、获得自信与自觉、敢于失败、体面输赢、适时示弱、放弃与选择、成长与适应、拒绝抱怨、扛住失败、不忘初心、取悦自己等多个方面,帮助读者在挫折中成长,赢得幸福人生。 链接: https://pan.quark.cn/s/b05aae0bc3a1 🏷标签: #成功勵誌 👥 群组:@BooksRealm
标题:纽约文学地图 [外國文學] 简介: 本书以文学为钥匙,穿行于19世纪至当代的纽约街区、码头、桥梁与剧院,探寻移民文化与时代浪潮中塑造的文学脉络。以曼哈顿、布鲁克林等地理单元为线索,描绘惠特曼、金斯伯格等作家的足迹,揭示格林威治村、百老汇等地标如何孕育影响世界的文学声音,并梳理哈莱姆文艺复兴、垮掉的一代等思潮的兴起与演变。节奏明快,信息密集,让读者感受纽约特有的能量与呼吸。 链接: https://pan.quark.cn/s/fa26266441f3 🏷标签: #外國文學 👥 群组:@BooksRealm
标题:鸟有什么好看的 [科普百科] 简介: 用双脚步行、昼行性、靠视觉声音沟通、一夫一妻制——自然界只有鸟类和人类满足这些条件。本书从无人岛讲到外太空,从吸血鬼谈到恐龙,解答凤凰不死传说、红头绿鸠为何不红、乌鸦竟是第六种吸血鸟等奇趣谜题。二次元妄想鸟类学,一边爆笑一边学到鸟类的奥秘。 链接: https://pan.quark.cn/s/f4481b96327f 🏷标签: #科普百科 👥 群组:@BooksRealm
❤1
Telegram必备的搜索引擎,极搜JISOU帮你精准找到,想要的群组、频道、视频、音乐 👉 t.me/jisou2?start=a_843210799
标题:零边际成本社会 [經濟管理] 简介: 《第三次工业革命》探讨了生产力、协同共享、产消者等概念,描述数百万人生产生活模式的转变。产消者以近乎零成本分享信息、能源、3D产品,通过社交媒体零成本共享汽车、住房等。物联网连接数十亿人与组织,实现全球协同共享,其意义可能超过20世纪电气化。数字化经济中,使用权胜所有权,可持续取代消费,合作压倒竞争,共享价值替代交换价值。“零成本”现象催生混合经济模式,颠覆传统市场,我们正迈入全新经济领域。 链接: https://pan.quark.cn/s/414f52188971 🏷标签: #經濟管理 👥 群组:@BooksRealm
标题:欢迎来到一年级:幼小衔接家长手册(全新升级版) [教輔用書] 简介: 双减政策取消课后作业、考试和校外补习班后,家长如何合理规划孩子时间、安排每日学习成为关键。尤其对即将或刚进入一年级的孩子,这一年是规范学习的起跑点,将决定学习是乐趣还是负担。本书系统梳理一年级学生的学习、生活、社会性培养和天赋启迪,介绍该年龄段孩子的生理心理特点、学校教学要求及家校配合方案,帮助家长明确应培养哪些习惯、发展哪些能力、掌握哪些知识与技能,让孩子在学校和家庭密切配合中更好成长。 链接: https://pan.quark.cn/s/490bdb45e739 🏷标签: #教輔用書 👥 群组:@BooksRealm
标题:核医点睛·肿瘤追踪 [醫學養生] 简介: 本书是“核医点睛”系列科普图书的肿瘤分册,以问答形式图文并茂地介绍核医学显像基础、全身肿瘤筛查、各部位常见肿瘤显像要点及前沿技术进展。内容涵盖辐射安全、显像技术概念、检查方法及其在各大系统肿瘤中的应用,并解析新型分子探针与人工智能技术的最新进展。科学严谨、案例典型,兼具专业性与普及性,适合肿瘤患者、家属、公众及临床医师、医学生、健康工作者阅读。 链接: https://pan.quark.cn/s/b7c2dd631f31 🏷标签: #醫學養生 👥 群组:@BooksRealm
Showing the 12 most recent of 43 posts we hold for @BooksRealm. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Mentions
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 21 August 2026 — this entry's latest reading, not the date you are reading this.
“书之领域图书馆” (@BooksRealm), 15,009 subscribers as measured 21 August 2026. Telegram Register, tgregister.com/channel/BooksRealm.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.