4 measurements spanning 22 days, net -2. 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 515–517 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
28 Aug 2026, 19:36
515
-1
15 Aug 2026, 00:33
516
-1
6 Aug 2026, 18:32
517
no change
6 Aug 2026, 17:40
517
first reading
Engagement
8 posts held, back to 10 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 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
3.30%
avg views ÷ 515 subscribers
Avg views / post
17.0
1 post measured
Reaction rate
11.8%
reactions ÷ views · ER floor
Posts in window
1
of 8 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 4 August 2026
Posts held
8 (10 June 2026 – 4 August 2026)
Views total
17
Reactions total
2
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
6 Aug 2026, 18:32 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
35 reactions across 7 posts, in 4 distinct kinds. The most used accounts for 42.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
15
42.9%
🔥
9
25.7%
👍
7
20.0%
🥰
4
11.4%
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 7 of the 8 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 35reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 8 most recent posts we hold, published 10 June 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.
Охраняемые интеллектуальные права на картинки с ИИ.
Суд в Москве отказался признать сгенерированные ИИ изображения творчеством.
В чем проблема?
Авторство фотографий же никто не оспаривает??
Относительно недавно судебная практика пошла по пути признания ИИ как технического инструмента для создания объектов интеллекту прав.
Что не так в этот раз?
Автор сгенерированных в нейросети изображений "Мона Лиза с вином" и …
Невероятно красивая
Работа с голландской живописью, барокко в ДольчеГаббана, их читаемый ДНК, и 16-летняя дочь Венсана Касселя и Моники Белуччи - Леони Кассель, которая открыла традиционное шоу Dolce & Gabbana Alta Moda, - потрясающа.
Хороший вопрос который полезно себе задавать. Вот скоро будет середина лета.
Что я откладываю??
Что я не делаю?
Что мне мешает? «Почему?» я тоже задаю. Для меня это промежуточный вопрос. Это вскрывает море причин.. надуманных и не очень…
А потом - получается понять, нужно ли мне это вообще и если да то в каком варианте.
Что (или скорее кто?) мне помочь и ЗАЧЕМ на самом деле это нужно
Здесь это превращается в настоя…
У своей коллеги увидела такую мысль:
⚡️Мудрость дна: у крутейшего психолога должна быть супервизия - это гигиена..
У умнейшего собственника должен быть человек, который не даст свернуть с пути
Как жаль, что это не мои слова… Это собственно то, с чем я хожу последнюю неделю..
Что то около месяца назад я проводила эфир по кризису. Рассказывала, чем нынешняя ситуация отличается от того, что мы видели.
Сейчас подняла…
Другой пример миграции образа от плавных линий и достаточно мужественного образа до носика птички и образа пидореро.
Это когда не нужно гнаться за просто абстрактным изящным носиком, и относится это ко всем и а мужчинам и к женщинам.
Благо сейчас есть возможность примерить новый образ через ИИ.
Любитель я конечно обещать🙈🙈
Короче что я хотела сказать? Так посмотришь посмотришь трансформацию и понимаешь как нас колбасит 😅
Я тут - чистила телефон и залипла на своих эфирах 18-19 года)) интересно на стиль посмотреть
Однозначно, внутреннее состояние отражается во вне))
Что я про Киркорова хотела сказать. Я в феврале на вебинаре по мужской стилистике показывала его как образец барокко, массивные округлые лини…
Тут пишут про пластику Киркорова.
Завтра напишу про эстетику, носы и уникальность.
Движения души оставим психологам, посмотрим на картинки, воспою в очередной раз ОДУ природной лепке и эстетике 😄😄
По приглашению клуба DOMINIC
была сегодня на мероприятии, где много говорили про антикризисные меры. Про то что это:
▪️зона роста и пересборки (а у меня недавно было 2 эфира на эту тему!!)
▪️необходимости честного взгляда на себя и свой бизнес
▪️отказа от неработающих моделей и неэффективных сотрудников,
▪️внимание к цифрам и эффективности
Много говорили про энергию собственника, отдых, кайф и драйв как необходимые …
❤2
Signed Оксана Дегтярь
Showing the 8 most recent of 8 posts we hold for @codeofCulture. 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.
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.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@codeofCulture named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all.A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@codeoftyle named in 1 post, 8 August 2026 – 8 August 2026
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 28 August 2026 — this
entry's latest reading, not the date you are reading this.
“Арт-дама вправе” (@codeofCulture), 515 subscribers as measured 28 August 2026. Telegram Register, tgregister.com/channel/codeofCulture.
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.
