2 measurements taken within a single day. 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 60–62 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
17 Oct 2026, 03:15
61
no change
16 Oct 2026, 19:22
61
first reading
Engagement
8 posts held, back to 2 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 1 page of Telegram’s post history, 20 posts per page.
ERR · 30 days
17.6%
avg views ÷ 61 subscribers
Avg views / post
10.7
7 posts measured
Reaction rate
28.0%
reactions ÷ views · ER floor
Posts in window
8
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. It is computed over the 5 of 7 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 15 October 2026
Posts held
8 (2 October 2026 – 15 October 2026)
Views total
75
Reactions total
14
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
16 Oct 2026, 19:22 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
Video runtime
7s
Average length
7s
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
14 reactions across 5 posts, in 7 distinct kinds. The most used accounts for 28.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
💯
4
28.6%
❤
3
21.4%
👍
2
14.3%
😁
2
14.3%
🎉
1
7.14%
👏
1
7.14%
🔥
1
7.14%
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 5 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 14 reactions 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 2 October 2026 to 15 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.
Здравствуйте, участники Лабы БИ.
А у нас близится новая междисплинарная экспедиция.
На этот раз работаем по книге Беттина Гёшль | Клаус-Петер Вольф «Детективы Северного моря»
Чем нам интересны детективные истории? Развиваем критическое мышление, учимся смотреть на вещи нестандартно, погружаемся в тайны.
Но это еще не все. Нам ведь интересно узнать что-то новое.
В этот раз:
➡️ рассмотрим факты про фальшивые деньг…
КЛУБЫ с историями для детей и подростков pinned «Подробнее про два направления занятий для детей и подростков ⬅️ Лаборатория БИ - Большая исследовательская Междисциплинарные экспедиции через книжные истории Каждую неделя новая книжная история как портал в разные науки и области знания. Исследования, эксперименты…»
Подробнее про два направления занятий для детей и подростков
⬅️ Лаборатория БИ - Большая исследовательская
Междисциплинарные экспедиции через книжные истории
Каждую неделя новая книжная история как портал в разные науки и области знания.
Исследования, эксперименты, дискуссии, творчество, игры, задания, в которых нет одного правильного ответа.
Развиваем исследовательское и креативное мышление
ПОДРОБНЕЕ https://lab…
Здравствуйте, участники Лабы БИ.
Рассказываю, что происходило в очередной экспедиции.
Мы взяли в работу два произведения Джанни Родари из цикла “Сказки, у которых три конца”:
➡️ “Собака, которая не умела лаять”
➡️ “Большая морковка”
и одно произведение из цикла “Пестрые сказки” - “Лиса-фотограф”.
🐶“Собака, которая не умела лаять”:
📌Зоология и коммуникация: посмотрели презентацию и обсудили две темы - 1) язык, как…
В книге Носова Незнайка, Кнопочка и Пестренький на перекрестке решают, в какой город поехать: Каменный, Земляной или Солнечный.
Знак - проезжающий необычный автомобиль решил спор: поехали в Солнечный.
А мы с ребятами использовали Лего, чтобы построить свой город для дальнейшего путешествия Незнайки и К.
Вопрос не в архитектуре, а в придумывании таких устройств, мест, инструментов, технологий и существ, которые пом…
Нужно ли быть готовым, что в руках окажется волшебная палочка?
Здесь однозначного ответа. Но точно, желательно иметь желания, мечты, надежды.
Как показала практика, они могут быть не обязательно о себе, не для себя.
А вот более сложный уровень - как использовать волшебную палочку для решения серьезных человеческих вопросов. С чем работали, продолжая держать в руках ВП:
🪄В океане много пластика
🪄Пожилым людям слож…
Здравствуйте, участники Лабы БИ.
Следующее занятие пройдет по книге Николая Носова «Незнайка в Солнечном городе».
Многие знают историю про Незнайку по первой книге - «Незнайка в Цветочном городе». Но нам для занятия больше подходит отправиться с главным героем в футуристический город и попробовать обзавестись волшебной палочкой.
А еще мы будем использовать на занятии конструктор Лего. Как же в футуристическом город…
Showing the 8 most recent of 8 posts we hold for @kidsstorytell. 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
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 17 October 2026 — this
entry's latest reading, not the date you are reading this.
“КЛУБЫ с историями для детей и подростков” (@kidsstorytell), 61 subscribers as measured 17 October 2026. Telegram Register, tgregister.com/channel/kidsstorytell.
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.