Literature — 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 13 September 2026 and assigned it the closest of 31 fixed categories, at 100% 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
13 measurements spanning 40 days, net +3,273. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 1,763–6,018 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
16 Sept 2026, 11:37
5,527
+853
12 Sept 2026, 09:21
4,674
-99
7 Sept 2026, 21:19
4,773
-58
2 Sept 2026, 14:46
4,831
-138
30 Aug 2026, 11:57
4,969
+961
27 Aug 2026, 11:45
4,008
-91
24 Aug 2026, 19:19
4,099
+50
20 Aug 2026, 19:23
4,049
+1,056
18 Aug 2026, 00:18
2,993
+32
14 Aug 2026, 21:55
2,961
-70
11 Aug 2026, 16:28
3,031
+745
8 Aug 2026, 11:47
2,286
+32
7 Aug 2026, 17:32
2,254
first reading
Engagement
20 posts held, back to 25 July 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 1 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 7 August 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
621 reactions across 20 posts, in 8 distinct kinds. The most used accounts for 67.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🍓
418
67.3%
💘
139
22.4%
🕊
29
4.67%
💋
18
2.90%
🐳
7
1.13%
😭
6
0.966%
💅
3
0.483%
🎃
1
0.161%
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 20 of the 20 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 621 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 25 July 2026 to 7 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.
Silas Marner by George Eliot
سرنوشت سایلاس مارنر که به خاطر یه تهمت اشتباه از جامعه طرد میشه و ناچار میشه به یه شهر دور بره. اوایل داستان اونقدرا جذبم نکرد ولی هرچقدر جلوتر رفت و شخصیتهای بیشتری معرفی شدن بیشتر عاشق کتاب شدم. به خصوص بزرگ شدن هپزیبا و ائرن رو خیلی دوست داشتم و کمکم شخصیت سایلاس هم تونست جذبم کنه. نسبت به میدلمارچ داستان سادهتریه ولی خیلی شیرین و تابستونیتر. من بیشتر از میدلمارچ دوستش داشتم و لا…
سیری در آثار جورج الیوت 🍎
جورج الیوت (۱۸۱۹–۱۸۸۰)، نام ادبی مری آن اوانز، یکی از مهمترین رماننویسان دورهی ویکتوریاست؛ نویسندهای که آثارش را از مهمترین نمونههای رئالیسم در ادبیات انگلیس میدانند. رمانهای الیوت بیشتر از اتفاقات عجیبوغریب، دربارهی آدمهای معمولی، انتخابهایشان و تاثیری است که تصمیمهای ما روی زندگی خودمان و دیگران میگذارند.
• سرگذشت:
مری آن اوانز در خانوادهای نسبتا مرفه در وارویکشر بزرگ شد …
ژانر ادامهنویسی یا Spin-off☂
در ادبیات، به آثاری گفته میشود که دنیای رمانهای کلاسیک و محبوب را گسترش میدهند. این کتابها معمولا از زاویهدید شخصیتی دیگر روایت میشوند، به پیشینهی یک کاراکتر فرعی میپردازند یا داستان را پس از پایان کتاب اصلی ادامه میدهند و به سوالات بیپاسخ طرفداران پاسخ میگویند.
برخلاف 'بازنویسی مدرن یا Modern Retelling' که داستان را به عصر جدید میآورد، این آثار وفادار به فضای تاریخی و شخصی…
اولین جلسه بوککلاب با کتاب تابستان از ادیت وارتون👒
اگر شما هم دوست دارین یه جمع دوستانه داشته باشین که بتونین درباره کتاب صحبت کنین و دوستای جدید پیدا کنین، از اومدنتون خوشحال میشیم!
📍شیراز، ملاصدرا
🗓۱۷ مرداد ماه، ساعت ۱۷:۰۰ الی ۱۹:۰۰
☕️به صرف چای
هزینه: ۲۵۰ هزار تومان
اطلاعات بیشتر و رزرو @iichliwpmiya
Middlemarch by George Eliot
داستان شهری به اسم میدلمارچه که حول دو خانواده بروک و وینسی میچرخه. شخصیتپردازی خیلی خوبی داره و تونسته همه قشرها رو به تصویر بکشه. شخصیت دوروتیا و رازمند رو هم خیلی خوب در برابر هم قرار داده. حتی بخش عاطفی و رمنس داستان رو هم به خوبی پیش برده و تفاوت بین love language هر کاپل خیلی واضحه. با وجود حجم زیادش، به خاطر روان بودن روند پیشروی داستان اصلا به چشم نمیاد. خیلی دوستش داشتم و قطعا…
🍓20🕊5
Showing the 12 most recent of 20 posts we hold for @MeadowOfPoppies. 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.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 3 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
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 16 September 2026 — this
entry's latest reading, not the date you are reading this.
“Meadow of Poppies” (@MeadowOfPoppies), 5,527 subscribers as measured 16 September 2026. Telegram Register, tgregister.com/channel/MeadowOfPoppies.
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.