Parenting & family — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 30% 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
27 measurements spanning 37 days, net +1. 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 17,420–17,464 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 27
Measured (UTC)
Subscribers
Change
11 Sept 2026, 15:39
17,431
+1
9 Sept 2026, 01:01
17,430
+5
5 Sept 2026, 17:18
17,425
-6
3 Sept 2026, 19:15
17,431
+3
2 Sept 2026, 07:45
17,428
+3
1 Sept 2026, 05:45
17,425
-4
31 Aug 2026, 04:38
17,429
+2
30 Aug 2026, 02:45
17,427
-4
29 Aug 2026, 01:16
17,431
+1
27 Aug 2026, 23:54
17,430
-6
27 Aug 2026, 00:37
17,436
-2
26 Aug 2026, 02:38
17,438
-1
25 Aug 2026, 03:45
17,439
-2
23 Aug 2026, 21:24
17,441
-4
22 Aug 2026, 05:46
17,445
-6
19 Aug 2026, 18:06
17,451
-1
18 Aug 2026, 17:32
17,452
-3
17 Aug 2026, 18:09
17,455
+4
16 Aug 2026, 14:52
17,451
-8
14 Aug 2026, 19:57
17,459
first reading
Engagement
73 posts held, back to 31 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 55 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
28.4%
avg views ÷ 17,431 subscribers
Avg views / post
4,960
48 posts measured
Reaction rate
2.08%
reactions ÷ views · ER floor
Posts in window
48
of 73 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.
What these figures were computed from
Window
Rolling 30 days · latest post in window 3 September 2026
Posts held
73 (31 July 2026 – 3 September 2026)
Views total
237,949
Reactions total
4,957
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Sept 2026, 09:18 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
Video runtime
10m 36s
Average length
1m 31s
Measured directly from 7 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
7,193 reactions across 73 posts, in 12 distinct kinds. The most used accounts for 41.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
2,952
41.0%
🙏
1,576
21.9%
👍
1,227
17.1%
🔥
1,007
14.0%
💯
150
2.09%
👎
93
1.29%
😁
68
0.945%
⚡
50
0.695%
😢
38
0.528%
🤯
14
0.195%
custom 5471878748460571181
11
0.153%
👏
7
0.097%
Custom emoji. One row above is a 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 count beside it is 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 73 of the 73 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 7,193 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 73 most recent posts we hold, published 31 July 2026 to 3 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.
Telegram Stars
Stars received
84
across the posts below
Posts paid on
18
of 73 we hold a reading for · 25%
Most on one post
23
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @denissamarin. 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 73 most recent posts we hold for this entry, published 31 July 2026 to 3 September 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.
#52_книги_в_год #утренняя_звезда
Друзья, хочу представить вам Кевина Крекер из Новосибирска. Он участвует в проекте «52 книги в год» с 1 января. Сейчас идет 36-я неделя — к этому времени по правилам нужно было прочитать 36 книг. У Кевина копился долг примерно в 15 книг.
Перед началом учебного года мы просили ребят закрыть долги, чтобы в школе было легче. Кевин справился за одну неделю. В один из дней он просидел с …
Дорогие друзья, особенно те, кто живёт за пределами России!
Наш детский журнал «Лесенка» выходит ежемесячно. Каждый выпуск можно скачать на Patreon за 3 доллара и распечатать для своих детей.
Также вы можете оформить ежемесячную подписку на Patreon — тогда новые выпуски журнала будут доступны вам в рамках подписки.
Сегодня я выложил сентябрьский номер
Ссылка: https://www.patreon.com/c/densam
#утренняя_звезда
Друзья, чтобы не повторяться по поводу каких-то активностей, которые проходят у нас в «Утренней звезде», я буду иногда рассказывать о некоторых направлениях немного подробнее.
Сегодня хотелось рассказать про группы английского языка, которые ведет Ирина Домбровская. Многие из нас учили английский язык десять лет в школе, но так и не заговорили: частая смена преподавателей, недостаточное количество …
#Благодарность
«Уважаемые представители фонда "Две лепты", дорогие благотворители, все неравнодушные люди!
От лица всей нашей семьи я хочу выразить глубочайшую признательность всем, кто принял участие в сборе средств на реабилитацию моего сына Артёма.
Цель достигнута — необходимая сумма собрана🙏 . Это стало возможным только благодаря объединению усилий сотен людей. Каждый ваш вклад, каким бы он ни был по размеру, с…
Мой август
Август оказался для меня месяцем, который очень сильно выбился из обычного графика. Было две большие поездки. За месяц я произнёс 21 проповедь, и подготовка к ним заняла практически всё свободное время.
Мой читательский август
1. Владимир Сурдин. «Космос без мифов. От НЛО до астрологических прогнозов» — 384 страницы. Дочитал. В прошлом месяце было прочитано 47%.
2. «Когда мой мозг спит. Сновидения с то…
#бесплатная_реклама
Репетитор по обществознанию и истории – подготовка к ОГЭ, ЕГЭ, МЦКО и устному экзамену!
Здравствуйте! Меня зовут Семён Михайлович, я действующий учитель истории и обществознания с 10-летним педагогическим стажем (из них 8 лет – непосредственно в должности учителя). Работаю в московской школе, ежегодно готовлю выпускников к ОГЭ и ЕГЭ. Моя квалификация подтверждена независимой диагностикой: в нояб…
Друзья, хочу сказать несколько слов о комментариях.
Под некоторыми моими публикациями иногда разворачиваются настоящие баталии. Я совершенно не против обсуждений, споров и разных точек зрения. Более того, считаю, что возможность спокойно обсуждать сложные вопросы — это хорошо.
Но я очень против того, когда обсуждение переходит в оскорбления, насмешки, грубость и унижение друг друга.
Меня даже спрашивали: почему я …
Книга Филиппа Никитина «Крещенные по вере» — редкий пример литературы о баптистах, обращенной к аудитории за пределами этой конфессии и позволяющей заглянуть в ее изолированный мир, вокруг которого существует множество предрассудков. О том, чем она может быть полезна не только верующим читателям, рассказывает Эдуард Лукоянов.
https://gorky.media/reviews/deti-otnyud-ne-kukuruzy
#готовлюсь_к_проповеди #мысли
По традиции сегодня наше богослужение будет посвящено детям, которые идут в школу. Я буду говорить о послушании.
Одна из ключевых мыслей моей проповеди — мы слушаемся человека, когда верим, что он знает больше нас и желает нам добра.
Я буду говорить, что Бог всезнающий и всеблагой, поэтому Ему можно доверять.
Это уже выходит за рамки проповеди для детей, но хочу оставить эту мысль …
Я много лет переживал и молился о том, чтобы в нашем братстве появлялись свои писатели и издавались свои книги. Я очень рад, что этот вопрос наконец сдвинулся с места. В последнее время немало братьев начинают писать. Недавно вышли книги Владислава Насонова и Александра Рыжова. Сейчас появилась ещё одна, уже очередная книга Михаила Голубина. Конечно, я не мог пройти мимо такого события. Я всеми силами поддерживаю это…
👍81❤63🔥23💯8🙏4👎1
Showing the 12 most recent of 73 posts we hold for @denissamarin. 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 1 registered channel — 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.
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.
Завтраки 🥨 Рецепты 🍳 @moi_zavtrak · 31,513 Telegram ranks this channel #70 of 72 here — alongside 71 others — read 6 September 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list 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 11 September 2026 — this
entry's latest reading, not the date you are reading this.
“Служение Дениса Самарина” (@denissamarin), 17,431 subscribers as measured 11 September 2026. Telegram Register, tgregister.com/channel/denissamarin.
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.