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 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.
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
3,130 average views per post against 1,325 subscribers — an engagement rate of 236.5%. Across the 54,164 registered channels in the same cohort — 1,000–3,162 subscribers, posting mainly in Russian — the middle half sit between 10.5% and 35.6%, with a median of 20.1%.
What this was computed from
Window
30 days (13 July 2026 – 12 August 2026)
Posts measured
9 of 9 published in the window (1 exact, 8 rounded by Telegram)
Views totalled
28,204
Mature posts only
236.5% 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 12 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
3 measurements spanning 3 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 1,325–1,326 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
9 Aug 2026, 08:51
1,325
-1
6 Aug 2026, 19:20
1,326
no change
6 Aug 2026, 16:13
1,326
first reading
Engagement
9 posts held, back to 17 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 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
236.5%
avg views ÷ 1,325 subscribers
Avg views / post
3,130
9 posts measured
Reaction rate
0.113%
reactions ÷ views · ER floor
Posts in window
9
of 9 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 8 of 9 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 4 August 2026
Posts held
9 (17 July 2026 – 4 August 2026)
Views total
28,204
Reactions total
28
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
6 Aug 2026, 16:13 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
28 reactions across 8 posts, in 7 distinct kinds. The most used accounts for 57.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
16
57.1%
🙏
3
10.7%
custom 5262708734429257538
2
7.14%
❤🔥
2
7.14%
👍
2
7.14%
😍
2
7.14%
custom 5262879498033979539
1
3.57%
Custom emoji. 2 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 areTelegram’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 8 of the 9 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 28reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 9 most recent posts we hold, published 17 July 2026 to 4 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.
Лето еще не закончилось — и сериалы тоже.
Если хочется чего-то уютного, смешного или просто расслабляющего, вот три отличных варианта. 👍
❤️ Забайкальский кинофестиваль в «Макс»
Боевик, который стал самым кассовым советским фильмом.
Становилось культовым, расходилось на цитаты и снято было так, что пересматривать хочется даже спустя долгие годы,
В одной из рубрик нашего канала будем рассказывать вам о картинах, которые не теряют своей актуальности, а сюжетный поворот вновь и вновь притягивает к экрану.
Так, фильм «Пираты XX века» в этом году празднует 45-летие с момента выхода в кинотеатр…
Ещё одна картина внеконкурсной программы ЗМКФ — документальный фильм «Восьмой свист морского зайца».
Режиссёр Владимир Марин отправился на Белое море и в Архангельскую область, чтобы рассказать о работе российских океанологов.
В центре сюжета — изучение морских млекопитающих и недавно обнаруженный восьмой тип свиста у крупного тюленя, местного «морского зайца». Камера фиксирует редкие звуковые записи, и режиссёр п…
Продолжаем делиться картинами из конкурсной программы ЗМКФ. На этот раз «Златовласка» из конкурса «Новый взгляд».
Чешское фэнтези для всей семьи по мотивам сказки Карела Яромира Эрбена. Режиссёр Ян Тешитела снял тёплую и светлую историю, которая вызывает улыбку.
Действие начинается в пушистых лесах и на солнечных полянах. Оленята бродят по тропам, овцы пасутся в полях, реки падают в водопады с радугами, в небе ловя…
🚩 А вот и победитель первого интерактива @zmkf_kinofest.
Первой собрала картинку и отгадала название фильма Софья.
Правильный ответ, конечно же, фильм Николая Лебедева «Легенда №17».
Админ свяжется с победительницей в течение дня.
📎 Теперь мы будем чаще проводить такие розыгрыши, оставайтесь с нами.
〰️ Сегодня день рождения отмечает заслуженная артистка России Нонна Гришаева.
Читинские зрители хорошо помнят ее по IX Забайкальскому международному кинофестивалю, который прошел в мае 2022 года. Тогда актриса стала одной из главных звезд фестиваля и вместе с Александром Олешко провела церемонию открытия.
Широкой публике Нонна Гришаева известна по пародийному шоу «Большая разница», сериалам «Папины дочки» и «Люба, …
В кино бесплатно хотите?
@zmkf_kinofest подарит два билета с открытой датой в «Удокан» любителю фильмов, который соберет в комментариях картинку и угадает откуда этот кадр.
➡️ Подсказка: режиссёр картины в этом году был председателем международного жюри ЗМКФ.
Итоги объявим во вторник.
❤️ ЗМКФ — 2026
Легенды!
За 90 лет своего существования студия «Союзмультфильм» выпустила более 1,5 тысячи мультфильмов.
Собрали подборку самых легендарных. Те, которые смотрел каждый.
Кажется, сейчас самое время, чтобы на чуть-чуть окунуться в детство.
❤️ Забайкальский международный кинофестиваль
❤1
Showing the 9 most recent of 9 posts we hold for @zmkf_kinofest. 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.
Citation-graph rank
Citation-graph rank — 595,577 of 1,151,006entries 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 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.
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 9 August 2026 — this
entry's latest reading, not the date you are reading this.
“Забайкальский международный кинофестиваль (16+)” (@zmkf_kinofest), 1,325 subscribers as measured 9 August 2026. Telegram Register, tgregister.com/channel/zmkf_kinofest.
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.
