Parenting & family — 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 98% 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.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Views per post sit far above this size band
25,100 average views per post against 26,210 subscribers — an engagement rate of 95.9%. Across the 18,383 registered channels in the same cohort — 10,000–31,614 subscribers, posting mainly in Russian — the middle half sit between 4.84% and 18.0%, with a median of 9.36%.
What this was computed from
Window
30 days (23 August 2026 – 22 September 2026)
Posts measured
18 of 18 published in the window (0 exact, 18 rounded by Telegram)
Views totalled
452,400
Mature posts only
95.9% over 18 posts read at least 24h after publication
When this is recorded. A channel is listed here only when its engagement rate sits at or above the 99th percentile of its cohort and is at least 3× away from that cohort’s median — above it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal. A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the key err_high, last confirmed 22 September 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Growth
33 measurements spanning 43 days, net -1,407. 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 25,043–28,337 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 33
Measured (UTC)
Subscribers
Change
19 Sept 2026, 17:58
26,210
-1,052
17 Sept 2026, 06:57
27,262
-198
15 Sept 2026, 03:58
27,460
+333
13 Sept 2026, 11:38
27,127
-830
11 Sept 2026, 14:37
27,957
+518
8 Sept 2026, 19:37
27,439
+131
5 Sept 2026, 10:39
27,308
-266
3 Sept 2026, 12:42
27,574
+993
2 Sept 2026, 08:04
26,581
-145
1 Sept 2026, 07:04
26,726
+443
31 Aug 2026, 06:34
26,283
-142
30 Aug 2026, 06:06
26,425
-205
29 Aug 2026, 02:55
26,630
-213
28 Aug 2026, 05:03
26,843
+456
27 Aug 2026, 08:06
26,387
-105
26 Aug 2026, 06:42
26,492
+351
25 Aug 2026, 05:54
26,141
+474
24 Aug 2026, 08:57
25,667
-243
22 Aug 2026, 17:14
25,910
-673
21 Aug 2026, 05:35
26,583
first reading
Engagement
46 posts held, back to 17 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 59 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
95.9%
avg views ÷ 26,210 subscribers
Avg views / post
25,100
18 posts measured
Reaction rate
0.469%
reactions ÷ views · ER floor
Posts in window
18
of 46 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 14 September 2026
Posts held
46 (17 July 2026 – 14 September 2026)
Views total
452,400
Reactions total
2,123
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
19 Sept 2026, 16:23 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
5,545 reactions across 46 posts, in 15 distinct kinds. The most used accounts for 32.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,779
32.1%
👏
1,128
20.3%
🔥
836
15.1%
🙏
803
14.5%
👍
691
12.5%
🥰
188
3.39%
💯
45
0.812%
🤝
22
0.397%
🎉
19
0.343%
👎
10
0.18%
🤔
9
0.162%
😁
8
0.144%
👌
4
0.072%
🕊
2
0.036%
😍
1
0.018%
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 46 of the 46 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 5,545 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 46 most recent posts we hold, published 17 July 2026 to 14 September 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.
Telegram Stars
Stars received
7
across the posts below
Posts paid on
4
of 46 we hold a reading for · 9%
Most on one post
3
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @Academy_of_Thought. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 46 most recent posts we hold for this entry, published 17 July 2026 to 14 September 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Скрытая выгода
или как не быть "жертвой обстоятельств"
Женщина по своей природе многозалачна, однако она часто теряет себя этом.
Поэтому стоит разобраться, почему вы решили, что без вас не справятся
Если вы контролируете всё: проект на работе, ремонт у родителей, расписание детей и настроение партнера.
То не удивляйтесь, что вы падает без сил, и не выдерживаете эмоций.
❌ Ловушка гиперконтроля и синдром «Я сама»…
Топ-5 мифов о здоровых отношениях.
Спойлер: ваша пара – не идеальна, и это прекрасно😏
Я много лет наблюдаю за парами – знакомыми, подписчиками, героями статей. И меня поражает, как мы делаем себя несчастными, сравнивая свои отношения с чужой картинкой. В соцсетях полно советов: «делай так», «идеальная пара делает вот это». Мы верим, а потом думаем: «у нас что-то не так».
Выдохните. Ваши отношения не обязаны быть и…
Все мы проходим через расставания.
И часто слишком острые эмоции толкают нас к одному лишь решению: вернуть засранца любой ценой. А часто этого делать ни в коем случае нельзя - как нельзя надеяться, что прокисший йогурт изменился и стал пригодным (хотя это правда - он изменился).
Так происходит потому что слишком долгое пребывание в стрессе невыносимо для нашей психики. А как справиться со стрессом расставания никто…
Представь себе... Ты стоишь на определённом участке жизни, с лицом «я взрослая, осознанная личность», а внутри тебя все клокочет: «Он не ответил на сообщение - неужели он не позвонит?»
Бывало? Если да, то... Ставим лайк и продолжим...
Знаешь, в этой ситуации тебе не должно быть стыдно. Ведь, с точки зрения нейробиологии это вообще не про отношения... Да, да. Здесь про эволюцию: наш мозг заточен на то, чтобы видеть …
Куда направить силы, чтобы жизнь поехала с другой скоростью?
Бывает, что мы упираемся в одну и ту же тему - не складываются отношения, не получается наладить контакт с окружающими. Постоянно чувство усталости или подавленности.
Кажется, что жизнь застыла на одном месте.
И тогда все внимание направляется именно туда, где болит. Происходит поиск причины, копание глубже, анализ, разбор себя по частям с надеждой: «Ну…
💔 Почему ваш муж резко стал «плохим папой», а вы превратились в «мамочку»?
Частая история: женщина уходит в декрет или с головой погрязает в детской рутине (уроки, кружки, быт). И вдруг ловит себя на мысли, что партнер ее дико раздражает. Он кажется незрелым, безответственным, или, наоборот, слишком контролирующим.
Как эксперт по МАК и трансформационным играм, я постоянно вижу этот сценарий на сессиях. В психологии …
Showing the 12 most recent of 46 posts we hold for @Academy_of_Thought. 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
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 19 September 2026 — this
entry's latest reading, not the date you are reading this.
“Академия Мысли|Консилиум” (@Academy_of_Thought), 26,210 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/Academy_of_Thought.
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.
