Film & TV — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 11 August 2026 and assigned it the closest of 31 fixed categories, at 99% 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.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Views per post sit far above this size band
5,800 average views per post against 4,535 subscribers — an engagement rate of 127.9%. Across the 39,021 registered channels in the same cohort — 3,163–9,999 subscribers, posting mainly in Russian — the middle half sit between 6.95% and 25.5%, with a median of 13.7%.
What this was computed from
Window
30 days (18 July 2026 – 17 August 2026)
Posts measured
10 of 10 published in the window (1 exact, 9 rounded by Telegram)
Views totalled
58,025
Mature posts only
139.7% over 9 posts read at least 24h after publication
When this is recorded. A channel is listed here only when its engagement rate sits at or above the 99th percentile of its cohort and is at least 3× away from that cohort’s median — above it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal.A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the key err_high, last confirmed 17 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Growth
6 measurements spanning 11 days, net +50. 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 4,467–4,544 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
16 Aug 2026, 17:54
4,535
+26
13 Aug 2026, 01:38
4,509
+33
10 Aug 2026, 04:13
4,476
-7
7 Aug 2026, 00:26
4,483
-2
6 Aug 2026, 04:03
4,485
no change
6 Aug 2026, 02:16
4,485
first reading
Engagement
24 posts held, back to 24 June 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 6 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
127.9%
avg views ÷ 4,535 subscribers
Avg views / post
5,800
10 posts measured
Reaction rate
1.48%
reactions ÷ views · ER floor
Posts in window
10
of 24 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 7 August 2026
Posts held
24 (24 June 2026 – 7 August 2026)
Views total
58,025
Reactions total
858
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
8 Aug 2026, 18:03 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
4m 45s
Average length
1m 11s
Measured directly from 4 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
1,470 reactions across 19 posts, in 34 distinct kinds. The most used accounts for 32.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
😁
474
32.2%
🔥
342
23.3%
❤
207
14.1%
👏
111
7.55%
💯
90
6.12%
🤣
76
5.17%
✍
34
2.31%
🕊
29
1.97%
🤝
19
1.29%
🤔
11
0.748%
🤮
11
0.748%
🍓
7
0.476%
😐
7
0.476%
🤩
7
0.476%
👀
6
0.408%
🙈
6
0.408%
😨
4
0.272%
🎅
3
0.204%
😍
3
0.204%
🤬
3
0.204%
14 further kinds
20
1.36%
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 24 of the 24 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 1,933reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 24 most recent posts we hold, published 24 June 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.
✏️Давно не было хороших книгорекомендаций.
#кинокниги@kino_blokk
Недавно прошлась «по пыльным полкам» своей онлайн библиотеки и обнаружила незаслуженно забытую книгу Жиля Делёза.
«Кино» не просто исследование фильмов, а радикальная попытка создать философию кино как самостоятельную область мысли.
В первой части («Образ-движение») автор выстраивает классификацию образов, связывая их с кинематографическими приёмами и…
Шутки шутками, зато россияне снова обратили свой взор на нетленную классику.
«Уже за это можно сказать спасибо».
*это не утка, реальная публикация на РИА Новости
*Сова на фото как квинтэссенция экзистенциального ужаса
История возникновения системы звёзд.
Часть 1️⃣
Система звёзд в кино — это не просто набор известных имён, а целая индустриальная модель, которая определяет, как фильмы производятся, продаются и воспринимаются зрителями.
Её история начинается задолго до появления первых «иконических» лиц современных блокбастеров и напрямую связана с экономикой кинорынка.
В первые десятилетия кинематографа (1890-е начало 1900-х) кин…
Маркетинг, страх и связи: почему новые лица не пробиваются в кино.
Тоже часто ловите себя на мысли, что весь наш современный кинематограф держится на Борисове, Пересильд, Томе Холланде и Зендае? Честно, иногда путаюсь, какой проект и о чём смотрю, потому как вчера актёр был злодеем в блокбастере, а теперь жертва в драматической истории, а я ему по инерции не сопереживаю, потому что в моей голове он должен всех побед…
Я хочу смотреть «Одиссею» Нолана
Но у нас есть «Одиссея» Нолана Дома.
«Одиссея» у нас дома:
«Одиссея» по-русски: путь через пиратскую мясорубку
Ситуация с новым фильмом Кристофера Нолана «Одиссея» постепенно переходит в стадию чистого абсурда.
Для начала стоит отдать Нолану должное: он умеет превращать свои фильмы в события задолго до премьеры. Чего стоят хотя бы бесконечные споры вокруг кастинга и других творческ…
«Король-рыбак» Терри Гиллиама - это фильм о том, как глубокое падение может стать путем к искуплению.
Сюжет вращается вокруг Джека Лукаса, радиоведущего, чье неосторожное слово провоцирует трагедию. Потеряв всё, он встречает Перри - бездомного, который в той самой резне лишился любимой женщины. Перри живет в мире галлюцинаций и поиска Святого Грааля, и эта встреча становится для обоих шансом на спасение.
Главное ук…
Имеет ли кино право переписывать историю?
Есть два основных способа смотреть исторический фильм, и они разводят зрителей по разные стороны зала, как реки разводят берега.
Первый зритель садится в кресло, чтобы прожить историю - просто историю, с началом, героем и финалом. Для него экран - отдельная вселенная, живущая по законам драмы, а не по учебнику. Спросите его после сеанса про даты - он скорее всего пожмёт пле…
Внезапно, прерываю своё непозволительное молчание в канале таким вот роликом!
Простите, дел невпроворот, всё наобещанное выполним.
…
2 года охоты на спектакль, насильственный смотр, причем мне пришлось это сделать второй раз вопреки и против своей воли, но забыть и забить не получилось.
И шампанским не смыть.
Климу Александровичу тоже досталось. Страдали все.
Хотела бы я пожелать приятного просмотра, но это не тот с…
«Секретное досье» 2017
Стивен Спилберг.
Действие фильма разворачивается в начале 1970-х годов, в руки журналистов The Washington Post попадают секретные материалы Пентагона, доказывающие, что американское правительство на протяжении многих лет сознательно вводило общество в заблуждение по поводу войны во Вьетнаме.
Перед издательницей газеты и главным редактором встаёт тяжёлый выбор: подчиниться давлению власти и со…
🔥42✍22🤝5❤4🕊2💅1🤔1
Showing the 12 most recent of 24 posts we hold for @kino_blokk. 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.
Posts edited after publishing
@kino_blokk edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
8 August 2026
Most recent edit
8 August 2026
Citation-graph rank
Citation-graph rank — 248,905 of 1,481,502entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
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.
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.
Клим Жуков @klimzhukoff · 138,581 Telegram ranks this channel #3 of 88 here — alongside 87 others — read 13 August 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 16 August 2026 — this
entry's latest reading, not the date you are reading this.
“КиноБлок” (@kino_blokk), 4,535 subscribers as measured 16 August 2026. Telegram Register, tgregister.com/channel/kino_blokk.
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.
