Other / unclassifiable — 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 17 September 2026 and assigned it the closest of 31 fixed categories, at 58% 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
14 measurements spanning 42 days, net +54. 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 1,395–1,470 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
17 Sept 2026, 16:40
1,461
+3
13 Sept 2026, 17:38
1,458
-2
10 Sept 2026, 08:01
1,460
+11
5 Sept 2026, 12:19
1,449
+3
1 Sept 2026, 22:56
1,446
+2
30 Aug 2026, 09:04
1,444
+6
27 Aug 2026, 00:42
1,438
+5
24 Aug 2026, 06:56
1,433
+7
20 Aug 2026, 06:16
1,426
+12
16 Aug 2026, 21:38
1,414
+5
13 Aug 2026, 06:56
1,409
+5
10 Aug 2026, 15:48
1,404
-3
7 Aug 2026, 12:01
1,407
no change
6 Aug 2026, 17:48
1,407
first reading
Engagement
5 posts held, back to 28 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 5 posts for this entry, the most recent from 6 August 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
266 reactions across 5 posts, in 7 distinct kinds. The most used accounts for 45.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
custom 5467468839249798159
120
45.1%
custom 5283271452999587861
46
17.3%
❤
43
16.2%
custom 5283015872380705687
18
6.77%
custom 5323420837347364237
17
6.39%
custom 5280605287626084437
12
4.51%
custom 5280748696584098314
10
3.76%
Custom emoji. 6 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them are Telegram’s.
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 5 of the 5 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 266 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 5 most recent posts we hold, published 28 July 2026 to 6 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.
Telegram Stars
Stars received
2
across the posts below
Posts paid on
2
of 5 we hold a reading for · 40%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @polinoporeading. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 5 most recent posts we hold for this entry, published 28 July 2026 to 6 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
🤩🥺 Аааа как же я рада. В том году это было лучшим событием лета
Уже в эти выходные пройдет Гаражка МИФа в Калининграде. В прошлый раз я ушла оттуда со стопкой книг, потому что удержаться от таких цен было просто невозможно. Так что не зря недавно сделала анхол🤩
Кроме книг, также будет небольшой лекторий. Если планируете заглянуть, можно совместить приятное с полезным.
8 августа
13:00 — «Зачем выпускать нон-фикшн к…
[события последних дней]
Дочитываю третью часть «Разрушь меня», и пока она идет заметно медленнее предыдущих, как будто буксует 😎🤩
То ли настроение уже не то, то ли самой истории пока не хватает какого-то сильного поворота. Но для вас я продолжаю снимать влог, поэтому очень надеюсь, что уже на следующей неделе наконец-то его закончу.
🩶 На днях сходили с девчонками на выставку геометрической абстракции «Точка и лин…
🤩🤩🤩🤩🤩🤩🤩🤩🤩
за июль
Я побила свой рекорд и прочитала 10 книг за месяц. Сама в шоке, друзья. Последний раз такой масштаб был в октябре 2025, тогда я прочитала 9 книг⭐️
Вот как можно определить, что моя жизнь стала стабильнее и спокойнее. Конечно, некоторые книги небольшие, но сколько удовольствия я получила
Самый главный показатель успеха лично для меня — я взялась за большой цикл. Немного выпала из жизни, но зато см…
🤩🤎🤎🤎🤎🤎 🤎🤎🤎🤎🤎
Книжный анхол: расхламление
Сегодня вместе пройдемся по моим книжным полкам и решим, с какими 13 книгами пришло время попрощаться.
https://youtu.be/yzPlCF1kUFI
🎥🤩 Скорее смотрите и делитесь в комментариях по какому принципу решаете, какие книги остаются в вашей библиотеке?
Мы в книжном клубе, кажется, нашли книгу с самой ужасной аннотацией ☕️🍋
В июле нам всем хотелось чего-то легкого, солнечного и летнего. В итоге «Под солнцем Тосканы» стала первой книгой, которая почти всем не понравилась.
Все дело как раз в той самой аннотации. Она обещает историю о героине, которая после развода покупает виллу в Италии и заново учится жить.
А по факту это мемуары самой писательницы, путевые замет…
Showing the 5 most recent of 5 posts we hold for @polinoporeading. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
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 2 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 17 September 2026 — this
entry's latest reading, not the date you are reading this.
“POLINOPO • в читающей эре” (@polinoporeading), 1,461 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/polinoporeading.
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.