Personal blog — 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 21 September 2026 and assigned it the closest of 31 fixed categories, at 97% 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
5 measurements spanning 14 days, net -4. 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 419–426 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
21 Aug 2026, 15:36
420
-4
13 Aug 2026, 16:37
424
-1
8 Aug 2026, 05:20
425
no change
7 Aug 2026, 13:41
425
+1
7 Aug 2026, 08:48
424
first reading
Engagement
4 posts held, back to 30 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 4 posts for this entry, the most recent from 1 August 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
6s
Average length
6s
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
34 reactions across 4 posts, in 5 distinct kinds. The most used accounts for 55.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
19
55.9%
🥰
8
23.5%
💯
3
8.82%
custom 5312538279277502204
2
5.88%
👍
2
5.88%
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 4 of the 4 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 34 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 4 most recent posts we hold, published 30 July 2026 to 1 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.
2-х недельные каникулы в Москве
…случились у меня, моей мамы и братика, которые впервые прилетели ко мне в Москву.
если говорить про наш совместный отдых, то это было замечательно!
мы втроем так сплотились: всюду вместе гуляли, исследователи новые места в Москве, что-то пробовали, играли в игры, смотрели сериал, вместе готовили. И в этом столько тепла и любви.
кстати, маме Москва понравилась. 😁
сказала, что даже …
Коллеги, а вы уже почувствовали, что ретро-Меркурий наконец-то отпустил? 😄
Весь июль задачи давались сложнее обычного, коммуникации затягивались, многое шло совсем не так, как планировалось..
Последнюю неделю я вообще была без сил и энергии, буквально заставляла себя вставать.
А сегодня впервые за долгое время выбралась в люди: съездила на айда фест, встретилась с подругой, созвонилась с друзьями.
И такое ощущени…
Мой июльский арт-вечер: 15 новых выставок в Cube.Moscow
Еще в начале июля я побывала на открытии новых выставок в Cube.Moscow в самом Ritz-Carlton, куда меня пригласила моя коллега Арина 💓
Рассказать о них добралась только сейчас. Но лучше поздно, потому что не могу не поделиться своими впечатлениями)
15 выставочных проектов в «КУБе» современных художников, где у каждого проекта свое настроение и взгляд на привычн…
Фрилансер как микро-бизнес
У «Инк» вышла интересная статья с аналитикой, кейсами экспертов рынка о том, как фрилансеры конкурируют с агентствами».
⚡️Любопытный факт: среднемесячный доход фрилансеров вырос на ~25%, а каждая 3-я крупная компания уже работает с внештатными специалистами на постоянной основе.
На мой взгляд, за этими цифрами стоит более важный сдвиг — меняется в целом восприятие экспертного труда.
И…
❤4💯3
Showing the 4 most recent of 4 posts we hold for @duhovnyi_pr. 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.
Mentions
Names
Channels on the register whose handles appear in this channel's posts.
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 21 August 2026 — this
entry's latest reading, not the date you are reading this.
“Камила сочинила” (@duhovnyi_pr), 420 subscribers as measured 21 August 2026. Telegram Register, tgregister.com/channel/duhovnyi_pr.
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.
