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 26 September 2026 and assigned it the closest of 31 fixed categories, at 69% 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
6 measurements spanning 31 days, net +7. 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 116–127 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
9 Sept 2026, 09:56
126
+8
31 Aug 2026, 14:15
118
+1
24 Aug 2026, 16:42
117
-1
16 Aug 2026, 18:58
118
-1
10 Aug 2026, 06:53
119
no change
9 Aug 2026, 20:16
119
first reading
Engagement
6 posts held, back to 6 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 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 6 posts for this entry, the most recent from 30 July 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
1m 20s
Average length
1m 20s
Measured directly from 1 video 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
96 reactions across 6 posts, in 7 distinct kinds. The most used accounts for 28.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
custom 5249471473424296038
27
28.1%
custom 5426986105310306001
27
28.1%
🎉
23
24.0%
🔥
10
10.4%
❤
4
4.17%
🥰
3
3.13%
👏
2
2.08%
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 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 6 of the 6 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 96 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 6 most recent posts we hold, published 6 June 2026 to 30 July 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.
🎭Время зажигать софиты!
Друзья, до нового учебного года остались считанные дни, а наш творческий коллектив уже готов к яркому старту! Прежде чем сцена заполнится новыми событиями, предлагаем на мгновение обернуться назад.
Мы собрали для вас самые живые и искренние моменты нашего бэкстейджа. Ведь именно за кулисами рождается настоящая магия! Скорее включайте видео и ловите этот заряд вдохновения.
Приятного просмотр…
Гордимся нашими именинниками!🎩
Сегодня весь коллектив Студенческой театральной студии "ЛГУН" поздравляет с днём рождения нового представителя нашей команды - Кирилла Евстигнеева!
Кирилл стал частью нашего коллектива весной этого года и уже успел выступить со всеми на сцене!🎭
Дебютом для Кирилла стала роль Алджернона Монкрифа в спектакле по пьесе Оскара Уайльда «Как важно быть серьезным». Во время репетиций он пока…
🎩 Гордимся нашими именинниками!
Сегодня весь коллектив Студенческой театральной студии "ЛГУН" поздравляет с днём рождения Варвару Павлову!
Варя стала частью нашего коллектива в 2023 году, и вот уже третий год трудится в нашей труппе!🎭
За это время Варя успела принять участие в спектакле «Свидетельские показания», нескольких поэтических вечерах, литературной композиции «Тревожной памяти дозор» и спектакле «Как важн…
Гордимся нашими именинниками!🎩
Сегодня весь коллектив Студенческой театральной студии "ЛГУН" поздравляет с днём рождения Михаила Зайцева!
Михаил стал частью нашего коллектива ещë в 2018 году и уже восьмой год является актëром нашей театральной труппы!🎭
За это время Михаил успел принять участие в таких постановках как "Кое-что о том самом и не только", " Свидетельские показания", "Тревожной памяти дозор", «Как важн…
🎩Гордимся нашими именинниками!
Сегодня весь коллектив Студенческой театральной студии "ЛГУН" поздравляет с днём рождения Елизавету Щербакову!
Лиза пришла к нам в 2024 году. С самого своего прихода она помогала создавать магию на сцене с помощью работы со светом, сама принимала участие в поэтических вечерах и конкурсах. Лиза играла главную роль в нашем номере «Моргинцесса» на студенческом фестивале «Студвесна»! 🎭
…
🎩Театральная студия "ЛГУН" завершила свой очередной сезон!
Отгремел спектакль по пьесе Оскара Уайльда "Как важно быть серьёзным". Двойная жизнь английских джентельменов подошла к концу, а мисс Призм наконец-то нашла свой саквояж. А пока вы смотрите фотографии со спектакля, хотелось бы сказать несколько слов.
Спасибо, дорогие зрители, что в этом сезоне смеялись вместе с бенберистом Алджерноном Монкрифом, размышляли …
Showing the 6 most recent of 6 posts we hold for @lgun_theatre. 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.
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 September 2026 — this
entry's latest reading, not the date you are reading this.
“ЛГУН. Закулисье” (@lgun_theatre), 126 subscribers as measured 9 September 2026. Telegram Register, tgregister.com/channel/lgun_theatre.
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.
