书名:《追凶:哈佛一桩谋杀案和半个世纪的沉默》 ——一桩半个世纪前的凶案,与哈佛校园中的性别歧视 作者:[美] 贝基·库珀 格式:#mp3 #pdf 分类:#法律 #刑侦 #纪实文学 这本书能为你 1.详细揭开美国历史上的知名迷案,简·布里顿凶杀案的来龙去脉与侦破过程,追寻尘封半个多世纪的真相。 2.以案情为突破口,深度揭露哈佛大学等美国知名高校根深蒂固的性别歧视传统,以及女性研究者遭遇的不公。 📡音频:点击收听

Channel
每天听本书<听书|课程分享>
@tingshushare
On this record: Topic · Growth · Engagement · Reactions · Posts · Telegram's recommendations · Cite this entry
12,986subscribers
+247 since we began measuring on 1 September 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1002100799341 |
|---|---|
| Type | Channel |
| Username | @tingshushare |
| Created | Between 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 1 September 2026 |
| Last confirmed live | 18 September 2026 |
| Measurements held | 10 |
| Confirmed unchanged | 1 time, most recently 18 September 2026 |
| On Telegram | t.me/tingshushare |
Topic
Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 16 September 2026 and assigned it the closest of 31 fixed categories, at 55% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 18 Sept 2026, 07:19 | 12,986 | +39 |
| 15 Sept 2026, 23:42 | 12,947 | +23 |
| 14 Sept 2026, 03:20 | 12,924 | +24 |
| 12 Sept 2026, 12:59 | 12,900 | +31 |
| 10 Sept 2026, 13:36 | 12,869 | +45 |
| 7 Sept 2026, 07:00 | 12,824 | +43 |
| 4 Sept 2026, 11:35 | 12,781 | +14 |
| 2 Sept 2026, 23:37 | 12,767 | +17 |
| 1 Sept 2026, 21:55 | 12,750 | +11 |
| 1 Sept 2026, 05:31 | 12,739 | first reading |
Engagement
22 posts held, back to 12 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 4 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 7.32%
- avg views ÷ 12,986 subscribers
- Avg views / post
- 951
- 13 posts measured
- Reaction rate
- 0.149%
- reactions ÷ views · ER floor
- Posts in window
- 13
- of 22 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 6 of 13 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 2 September 2026 |
|---|---|
| Posts held | 22 (12 August 2026 – 2 September 2026) |
| Views total | 12,361 |
| Reactions total | 8 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 2 Sept 2026, 21:14 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.
Reaction mix
16 reactions across 11 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 16 | 100.0% |
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 11 of the 22 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 16 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 22 most recent posts we hold, published 12 August 2026 to 2 September 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
书名:《安史之乱》 ——大唐崩塌,盛世终结,在野心和阴谋之外,还有哪些原因? 作者:张诗坪 / 胡可奇 格式:#mp3 #pdf 分类:#历史 #唐朝 #高分必听 这本书能为你 1.详细复盘安史之乱从爆发到终结的历史进程,点评双方主要人物的决策与行动得失。 2.详解这场中唐历史变乱背后的深层政治社会经济原因,释读导致它爆发的历史必然性。 📡音频:点击收听
❤1
书名:《肥胖密码:少吃多动,为何还不瘦》 ——“少吃多动”还不瘦?肥胖是激素问题,不是热量问题。 作者:冯子新 格式:#mp3 #pdf 分类:#健康 #自然科学 #状态管理 这本书能为你 1. 揭示“少吃多动”反弹真相:1944年明尼苏达饥饿实验与2006年美国5万人7年追踪研究,直面节食减肥为何大概率反弹——你不是在和意志力作斗争,而是在和身体的内稳态机制作斗争; 2. 理解真正让你发胖的元凶:跳出热量计算的框架,看胰岛素如何把脂肪“锁”在细胞里,以及果糖、精制碳水、慢性压力如何悄悄拉高胰岛素水平; 3. 掌握间歇性禁食的底层逻辑:了解16:8禁食法为何不会降低代谢、反而能激活身体的燃烧模式。 📡音频:点击收听
❤2
书名:《人间烟火2.0:人类学家眼中的数字中国》 ——你在使用技术,其实技术也在使用你 作者:[英] 丹尼尔·米勒、王心远 格式:#mp3 #pdf 分类:#人类学 #AI #社会观察 这本书能为你 1.揭示算法的权力逻辑:谁是“标杆用户”,谁的内容被系统过滤——平台推给你的,从来不是中立的世界; 2.理解数字规训如何渗入日常:从高考生的24小时监控,到养老院的300项数据指标,看清量化管理如何替代人与人之间的真实连接; 3.发现人在技术缝隙里的主动性:恩施人用短视频强化当地价值观,草根创作者摸透算法逻辑——普通人从未停止驯服技术。 📡音频:点击收听
书名:《前浪后浪:近代中国知识分子的精神世界》 ——同一个时代,为何有人走向革命,有人走向沉默? 作者:许纪霖 格式:#mp3 #pdf 分类:#历史 #民国 #社会观察 这本书能为你 1.理解“文化惯习”:潜藏在情感、意志、性格里的底色,比立场更决定一个人的命运; 2.看懂晚清前浪的挣扎:从信奉“理”到顺应“势”,每一次妥协都是一次精神侵蚀; 3.读懂五四后浪的裂变:陈独秀、胡适、鲁迅,同代知识分子却有不同走向的根源; 4.区分两种对待主义的态度,不同态度造就不同的精神韧性。 📡音频:点击收听
❤1
书名:《从追赶向成熟:中国经济关键十年》 ——解码中国经济关键十年 作者:冯煦明 格式:#mp3 #pdf 分类:#经济学 #财富投资 #新趋势 这本书能为你 1.理解“从追赶向成熟”的核心框架,认识2026-2035关键十年的特殊性,在旧逻辑退潮、新逻辑显现的转型期把握方向; 2.掌握人口结构变化的三波婴儿潮逻辑、代际落差六七千万人的影响,理解服务业工业化、新能源与AI双轮驱动等产业趋势; 3.理解供强需弱的深层原因(制度设计、分配结构、房地产退潮),认识中国不会重演日本“失去三十年”的底层逻辑。 📡音频:点击收听
❤1
书名:《发现你的天赋》 ——你的缺点里,藏着你的顶级天赋? 作者:[日] 八木仁平 格式:#mp3 #pdf 分类:#职业发展 #思维方式 #自我提升 这本书能为你 1.学会用5个自我提问+3个他人视角,系统化地发现那些你“不知不觉就去做”的天赋动词; 2.掌握构建天赋地图的方法,把零散的优势整理成3-5个清晰的核心能力组合; 3.理解天赋×技能×兴趣的匹配公式,找到让你既擅长又热爱、做起来最自然的方向。 📡音频:点击收听
❤1
书名:《赌注:海难、叛变和谋杀的故事》 ——一艘漂流孤舰的遭遇,折射出怎样的人性考验 作者:[美] 大卫·格雷恩 格式:#mp3 #pdf 分类:#文学 #历史 #社会观察 这本书能为你 1.讲述一段堪比好莱坞大片,但真实发生的18世纪海难漂流之旅,看一群幸存者如何在无人荒岛奋力求生。 2.从故事当事人的行为抉择,分析其决策背后的社会心理与文化基因。一个社会与文化的韧性,如何在极端环境中得到验证? 📡音频:点击收听
书名:《简单致富2》 ——月薪不高、起点不好,也能实现财务自由? 作者:[美] J.L.柯林斯 格式:#mp3 #pdf 分类:#金融学 #理财投资 #个人生活 这本书能为你 1、分享一百个真实的财务自由故事——从8岁起就做童工的移民女孩,到月供339美元却攒出百万净资产的教师夫妇——看见这条路真实的模样; 2、理解为什么储蓄率比投资收益率更重要,学会用“双向加速”逻辑重新规划你的财务目标,找到比追涨杀跌更有效的致富路径; 3、了解适合中国普通人的指数基金实践框架,包括个人养老金账户的用法,建立一套“不折腾”的长期投资方案。 📡音频:点击收听
书名:《江南园林志》 ——如何用一个汉字看懂江南园林? 作者:童寯 格式:#mp3 #pdf 分类:#艺术 #历史 #睡前放松 这本书能为你 1. 记录1930年代江南园林的真实面貌,保存许多已消失园林的珍贵影像; 2. 讲述这本书的坎坷命运:从1937年完稿,到天津水灾受损,再到1963年出版的26年; 3. 呈现苏州拙政园、扬州个园、南京瞻园等名园的历史沿革与艺术特色。 📡音频:点击收听
书名:《工作社会的终结》 ——如果没有工作,你能定义自己吗? 作者:[德]乌尔里希·贝克 格式:#mp3 #pdf 分类:#社会学 #人文艺术 #热点问题 这本书能为你 1. 揭示“工作”是如何被神圣化的——为什么失业不仅丢收入,还会让人感觉丢脸; 2. 分析工作社会走向终结的两大根源:自反性现代化的反噬,以及资本逻辑与充分就业之间的致命悖论; 3. 理解AI、全球化、自动化不只是一场技术替代,背后有更深的社会结构变迁; 4. 提供重新定义工作、身份与人生意义的思路,在不确定时代找到自己的立脚点。 📡音频:点击收听
书名:《权力:为什么只为某些人所拥有》 ——在职场中,如何成为一个拥有权力的人? 作者:[美] 杰弗瑞·菲佛 格式:#mp3 #pdf 分类:#管理学 #商业 #社会观察 这本书能为你 1.移除压在职场人身上的“三块石头”:戳破“公平世界假设”的幻觉、看清“成功者建议”的幸存者偏差、放下“自我设限”的心理防御,让你不再原地踏步; 2.指出通往权力的三条实战路径: “选对战场”进入核心部门,“让自己被看见”建立声望,“掌握资源”进而获得权力; 3.看清权力背后的真实“价目表”:失去自主权、分不清真心、成瘾性——在踏上这条路之前,先看清代价。 📡音频:点击收听
Showing the 12 most recent of 22 posts we hold for @tingshushare. 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.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
@TG_book_data · 30,452
Telegram ranks this channel #3 of 44 here — alongside 43 others — read 8 September 2026
@ppbuzz_pro · 37,472
Telegram ranks this channel #11 of 20 here — alongside 19 others — read 1 September 2026
@readingclubus · 29,174
Telegram ranks this channel #12 of 41 here — alongside 40 others — read 8 September 2026
This channel appears in 3 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 18 September 2026 — this entry's latest reading, not the date you are reading this.
“每天听本书<听书|课程分享>” (@tingshushare), 12,986 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/tingshushare.
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.