Education — 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 10 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
59 measurements spanning 93 days, net -300. 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 14,565–14,955 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 59
Measured (UTC)
Subscribers
Change
8 Nov 2026, 08:50
14,610
-7
7 Nov 2026, 06:11
14,617
-2
6 Nov 2026, 08:16
14,619
-8
5 Nov 2026, 05:46
14,627
-4
4 Nov 2026, 08:19
14,631
-5
3 Nov 2026, 06:39
14,636
-1
2 Nov 2026, 08:37
14,637
-7
1 Nov 2026, 06:21
14,644
-3
31 Oct 2026, 09:44
14,647
-1
30 Oct 2026, 12:15
14,648
-6
29 Oct 2026, 15:17
14,654
-1
28 Oct 2026, 12:59
14,655
-15
27 Oct 2026, 10:21
14,670
-33
26 Oct 2026, 11:15
14,703
-2
24 Oct 2026, 17:30
14,705
+3
23 Oct 2026, 13:56
14,702
+1
22 Oct 2026, 15:26
14,701
-2
21 Oct 2026, 07:57
14,703
-4
20 Oct 2026, 03:37
14,707
-3
19 Oct 2026, 04:27
14,710
first reading
Engagement
22 posts held, back to 15 December 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 67 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
27.4%
avg views ÷ 14,610 subscribers
Avg views / post
4,000
2 posts measured
Reaction rate
2.46%
reactions ÷ views · ER floor
Posts in window
2
of 22 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 27 October 2026
Posts held
22 (15 December 2025 – 27 October 2026)
Views total
8,000
Reactions total
197
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
9 Nov 2026, 06:28 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.
What this channel posts
Photos
309
Videos
3
Links
121
Lifetime counters from Telegram’s own channel header, read 9 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Reaction mix
3,110 reactions across 22 posts, in 9 distinct kinds. The most used accounts for 79.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
2,469
79.4%
🔥
271
8.71%
🥰
126
4.05%
👍
111
3.57%
😍
88
2.83%
👏
29
0.932%
🤩
11
0.354%
😁
4
0.129%
🤗
1
0.032%
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 22 of the 22 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 3,110 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 22 most recent posts we hold, published 15 December 2025 to 27 October 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: 1 of 2 posts held from the last 30 days (50.0%) 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).
Дякуємо всім, хто вчора був на ефірі наживо, слухав і писав у чат 🤍
Якщо ви не встигли або хочете переглянути розмову ще раз, запис отримують учасники челенджу UnPause, частиною якого був наш ефір.
Взяти участь можна до 8 листопада: виконуйте завдання челенджу й отримайте доступ до запису.
https://t.me/unpause_challenge_bot?start=6ad8de057eff4935ff0b4964
Чи бувало у вас, що згадуєте себе кілька років тому і сумуєте?
За тією людиною, якою ви тоді були. Скільки в ній було енергії, бажань, сміливості.
А зараз ніби все те саме, але вже не те.
Влітку я записала два подкасти про втрату себе, і ваших коментарів під ними було стільки, що хочеться продовжити цю розмову. Цього разу наживо.
Сьогодні о 19:30 за Києвом — прямий ефір «Що робити, коли сумуєш за собою з минулого…
Знамениту схему ікігаю японці не впізнають
Ви точно її бачили: чотири кола, які перетинаються. Що ви любите. Що у вас добре виходить. За що вам платять. Що потрібно світу. У центрі, де сходяться всі чотири, живе ваше призначення. Знайдіть цю точку, і все стане на свої місця.
Тільки от намалював цю схему у 2011 році іспанський автор Андрес Зузунага й підписав словом purpose. Через три роки блогер подивився виступ на…
Про четверту новину з подкасту розкажу докладніше.
Коли якорі змінилися і старі відповіді на питання «хто я» більше не працюють, можна почати будувати нові — свідомо й покроково. Саме для цього є курс New ID.
За вісім модулів ми разом пройдемо шлях від відчуття «я себе загубила» до нових опор: цінностей, переконань, ролей і щоденних звичок, у яких ви себе впізнаєте.
На вас чекають відеоуроки, живі зустрічі зі мною…
Дякую вам за коментарі під вчорашнім подкастом. Їх було стільки, що я одразу записала другу частину.
Бо відчуття «я себе втрачаю» насправді має цілком конкретне пояснення.
У кожного з нас є якорі — те, через що ми себе впізнаємо. Наші ролі. Люди, які нас знають. Середовище, у якому ми живемо. Наші цінності, звички, навіть те, як виглядає звичайний день і де ми п'ємо каву.
Коли ці якорі зникають чи змінюються, з'яв…
Чи бувало у вас відчуття, ніби ви живете своє життя, але ви не зовсім у ньому?
Ви робите те, що треба.
Виконуєте ролі. Функціонуєте.
Але всередині є дивне відчуття:
“Це ніби не я і не моє життя.”
Найчастіше в такі моменти ми думаємо, що з нами щось не так. Що ми стали слабшими, втратили мотивацію, зламались або “втратили себе”.
Але, можливо, це не поломка.
Можливо, стара версія вас просто перестала працювати.
У …
Dream Year Mid-Year — 1 липня, 19:00
Програма підтримки для твоїх планів, цілей і бажань на 2026-й.
Всі подробиці: https://upgrade-yourself.com.ua/dream-mid-year
У позитивній психології є концепція mattering — «значущість». Це відчуття, що моє існування має значення для світу, і що я даю це відчуття іншим.
Ми звикли вважати головними джерелами страждання тривогу і стрес. Але дослідники додають ще одне — відчуття, що тебе не помічають. Прискорений ритм життя, соцмережі, штучний інтелект, який ось-ось замінить усіх. А часу сказати одне одному «я тебе бачу і чую» стає все менше.…
Ми звикли думати: спочатку — повір у себе, потім — почни діяти. А якщо порядок зворотній?
У новому випуску Happy Morning Show Алла розкриває термін Альберта Бандури — self-efficacy. Віра у власні сили не приходить першою. Вона народжується з маленьких дій, які ми вже зробили.
Дивіться повний випуск за посиланням:
https://www.instagram.com/reel/DYgjzWhMXQ6/
Якщо відгукнулося — поділіться з тими, кому це зараз потрі…
❤188👍27🥰9
Showing the 12 most recent of 22 posts we hold for @happyallaklymenko. 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 2 posts on @happyallaklymenko 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
3 November 2026
Most recent seen missing
3 November 2026
Median time before seen missing
3 months
Seen missing in the last 30 days
2
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 8 November 2026 — this
entry's latest reading, not the date you are reading this.
“Happy Alla” (@happyallaklymenko), 14,610 subscribers as measured 8 November 2026. Telegram Register, tgregister.com/channel/happyallaklymenko.
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.