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 12 September 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 the other topics.
Growth
22 measurements spanning 92 days, net +1,200. 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 5,464–7,082 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 22
Measured (UTC)
Subscribers
Change
5 Nov 2026, 19:51
6,895
+17
3 Nov 2026, 02:10
6,878
+5
30 Oct 2026, 22:04
6,873
+29
27 Oct 2026, 15:17
6,844
+23
24 Oct 2026, 13:09
6,821
+30
21 Oct 2026, 07:51
6,791
+19
17 Oct 2026, 21:56
6,772
+79
15 Oct 2026, 02:29
6,693
+164
12 Oct 2026, 05:00
6,529
+157
5 Oct 2026, 02:38
6,372
+576
26 Sept 2026, 04:17
5,796
+140
16 Sept 2026, 23:59
5,656
+5
12 Sept 2026, 20:17
5,651
-18
8 Sept 2026, 15:41
5,669
-9
3 Sept 2026, 00:38
5,678
-7
30 Aug 2026, 16:27
5,685
-6
30 Aug 2026, 12:19
5,691
no change
22 Aug 2026, 12:07
5,691
+4
15 Aug 2026, 20:25
5,687
-3
10 Aug 2026, 03:03
5,690
first reading
Engagement
21 posts held, back to 27 October 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 5 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
16.3%
avg views ÷ 6,895 subscribers
Avg views / post
1,120
20 posts measured
Reaction rate
0.903%
reactions ÷ views · ER floor
Posts in window
21
of 21 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 5 November 2026
Posts held
21 (27 October 2026 – 5 November 2026)
Views total
22,474
Reactions total
203
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
5 Nov 2026, 10:28 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
203 reactions across 19 posts, in 8 distinct kinds. The most used accounts for 56.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
115
56.7%
🔥
49
24.1%
👍
17
8.37%
😢
13
6.40%
🥰
5
2.46%
💘
2
0.985%
🎉
1
0.493%
👏
1
0.493%
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 20 of the 21 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 203 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 21 most recent posts we hold, published 27 October 2026 to 5 November 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.
Recent posts
Telegram’s own ‘edited’ marker: 2 of 21 posts held from the last 30 days (9.52%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
🫣05 ноября, четверг
1⃣🅾️1⃣ Григорий Мисютин, 11:00 по мск
Психологу тоже нужны люди: кто поддерживает тех, кто поддерживает всех?
Ссылка на КОНТУР: https://cnwhh882.ktalk.ru/app/stream/auditoriums/05edce89-3295-4c11-a310-c810197b83ea
1⃣🅾️2⃣ Люция Ибрагиммова, 13:00 по мск
Страшно ли ребёнку в закрытом центре?
Что происходит за закрытыми дверями?
Ссылка на КОНТУР: https://cnwhh882.ktalk.ru/app/stream/auditoriums/7d82…
🫣04 ноября, среда
9️⃣8️⃣ Екатерина Тучинская, 13:00, по мск (2 часа)
От концептуализации к терапии: поддерживающие циклы и план лечения.
Ссылка на КОНТУР: https://cnwhh882.ktalk.ru/app/stream/auditoriums/8a30c2d7-1a83-42f0-8a42-01193df96cbc
9️⃣9️⃣ Воскобой Мария, 16:00 по мск
Навык: "Противоположное действие"
Ссылка на КОНТУР: https://cnwhh882.ktalk.ru/app/stream/auditoriums/87397d83-1389-44d9-8e94-4b56f40db840
1⃣🅾…
Новый файл КАЛЕНДАРЯ для расписания на новую неделю.
Инструкция тут
https://t.me/konfaprl/614
❤️ Отдельная благодарность Юлии, повелительнице календарей: https://t.me/nekhoroshikh
@konfaprl
#календарь
Конференция «ПРЛ» pinned «Расписание эфиров на конференции 02.11-08.11: 🫣02 ноября, понедельник 9️⃣1⃣ Григорий Мисютин, 11:00 по мск (2 часа) Я могу это выдержать. Но хочу ли я так жить? Как построить свою систему навыков разобраться в себе и в мире. Ссылка на КОНТУР: https://cn…»
Расписание эфиров на конференции 02.11-08.11:
🫣02 ноября, понедельник
9️⃣1⃣ Григорий Мисютин, 11:00 по мск (2 часа)
Я могу это выдержать. Но хочу ли я так жить? Как построить свою систему навыков разобраться в себе и в мире.
Ссылка на КОНТУР: https://cnwhh882.ktalk.ru/app/stream/auditoriums/dccde1a1-a600-411f-9bd4-cda52c87e3e1
9️⃣2⃣ Григорий Мисютин, 13:00 по мск
Учеба по ДБТ
Ссылка на КОНТУР: https://cnwhh882.kta…
Александр Бегаев
Психолог
🎤17 октября, 14:00 по мск
Вместе с Екатериной Красногорской
Тема: Выгорание ДБТ терапевта: предикторы и профилактика
(уже прошло, а карточка спикера потерялась, исправляемся)
Работает в подходах когнитивно-поведенческой терапии (КПТ) и диалектической поведенческой терапии (ДБТ).
Помогает людям справляться с эмоциональными трудностями, лучше понимать себя и менять устойчивые модели мышле…
Мисютин Григорий
Дилеммы и полярности в терапии
Эта запись можно посмотреть:
https://boosty.to/konfaprl/posts/b14cd55e-4d17-4394-b272-66c4298ff9b0
Про Бусти:
https://t.me/konfaprl/622
✔️Про Григория
https://t.me/konfaprl/578
Наш чатик
https://t.me/konfaprlchat
🌐 РУТУБ
https://rutube.ru/channel/31422351/videos/
🌍 ВК-видео
https://vkvideo.ru/@konfaprl
🟠 Boosty
https://boosty.to/konfaprl
Эдуард Нелепко
Химические и поведенческие зависимости при ПРЛ: что между ними общего, чем отличаются и как из них выбраться
Эта запись можно посмотреть:
https://boosty.to/konfaprl/posts/13fcdb85-400d-4200-946c-8ac445b4b4c7
Про Бусти:
https://t.me/konfaprl/622
✔️Про Эдуарда
https://t.me/konfaprl/605
Наш чатик
https://t.me/konfaprlchat
🌐 РУТУБ
https://rutube.ru/channel/31422351/videos/
🌍 ВК-видео
https://vkvideo…
Елена Чернякевич, Екатерина Скоркина
Навыки при работе с травматичным опытом: протокол Мартина Бохуса при кПТСР
Эта запись можно посмотреть:
https://boosty.to/konfaprl/posts/badc3162-0cd0-47e1-8b3a-e47de425e54c
Про Бусти:
https://t.me/konfaprl/622
✔️Про Елену
https://t.me/konfaprl/644
✔️Про Екатерину
https://t.me/konfaprl/593
Наш чатик
https://t.me/konfaprlchat
🌐 РУТУБ
https://rutube.ru/channel/31422351/videos…
Евгения Чмутова
Поведение препятствующее терапии в работе с семьей в DBT
Эта запись можно посмотреть:
https://boosty.to/konfaprl/posts/106e4c43-4017-4673-b38e-137f937b1293
Про Бусти:
https://t.me/konfaprl/622
✔️Про Евгению
https://t.me/konfaprl/630
Наш чатик
https://t.me/konfaprlchat
🌐 РУТУБ
https://rutube.ru/channel/31422351/videos/
🌍 ВК-видео
https://vkvideo.ru/@konfaprl
🟠 Boosty
https://boosty.to/konfaprl
Евгения Чмутова
Как родители могут помочь своим детям с самоповреждающим и суицидальным поведением при прохождении DBT?
Эта запись можно посмотреть:
https://boosty.to/konfaprl/posts/4d683f0f-a926-4b6a-bdb3-ac6cc14ce375
Про Бусти:
https://t.me/konfaprl/622
✔️Про Евгению
https://t.me/konfaprl/630
Наш чатик
https://t.me/konfaprlchat
🌐 РУТУБ
https://rutube.ru/channel/31422351/videos/
🌍 ВК-видео
https://vkvideo.ru/…
Наталья Фомичева
Материнское насилие: как говорить о невыносимом
Эта запись можно посмотреть:
https://boosty.to/konfaprl/posts/3494a0c6-421a-436d-b7f3-cbd0f08b1efc
Про Бусти:
https://t.me/konfaprl/622
✔️Про Наталью
https://t.me/konfaprl/638
Наш чатик
https://t.me/konfaprlchat
🌐 РУТУБ
https://rutube.ru/channel/31422351/videos/
🌍 ВК-видео
https://vkvideo.ru/@konfaprl
🟠 Boosty
https://boosty.to/konfaprl
❤4
Showing the 12 most recent of 21 posts we hold for @konfaprl. 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 recorded as deleted after publishing
We recorded 1 post on @konfaprl as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
4 November 2026
Most recent seen missing
4 November 2026
Median time before seen missing
32 hours
Seen missing in the last 30 days
1
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 7 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.
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 5 November 2026 — this
entry's latest reading, not the date you are reading this.
“Конференция «ПРЛ»” (@konfaprl), 6,895 subscribers as measured 5 November 2026. Telegram Register, tgregister.com/channel/konfaprl.
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.