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 17 September 2026 and assigned it the closest of 31 fixed categories, at 62% 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.
Growth
12 measurements spanning 41 days, net +33. 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 1,539–1,590 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
17 Sept 2026, 10:59
1,578
-4
13 Sept 2026, 16:58
1,582
-2
4 Sept 2026, 01:41
1,584
+2
1 Sept 2026, 02:28
1,582
+2
28 Aug 2026, 19:22
1,580
+6
25 Aug 2026, 13:53
1,574
+8
22 Aug 2026, 13:34
1,566
+5
18 Aug 2026, 22:06
1,561
+4
15 Aug 2026, 11:59
1,557
+10
11 Aug 2026, 16:03
1,547
+2
7 Aug 2026, 21:32
1,545
no change
7 Aug 2026, 15:58
1,545
first reading
Engagement
6 posts held, back to 8 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 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 6 posts for this entry, the most recent from 17 July 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
1m 53s
Average length
38s
Measured directly from 3 videos 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
82 reactions across 6 posts, in 6 distinct kinds. The most used accounts for 63.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
52
63.4%
🔥
16
19.5%
👍
7
8.54%
👏
4
4.88%
🥰
2
2.44%
🤩
1
1.22%
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 6 of the 6 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 82 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 6 most recent posts we hold, published 8 June 2026 to 17 July 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.
🧩 Фрагменты индивидуальных занятий
Ваша любимая рубрика, в которой я показываю небольшие отрывки своих занятий с детьми и делюсь ссылками на игры, которые использую.
Это возможность подсмотреть идеи для домашних занятий, разобраться, какие навыки развивает каждая игра, и постепенно собрать свою коллекцию действительно полезных пособий для развития ребёнка.
На видео:
💗моталки (аналог)
💗«Времена года» Bondibon
💗прав…
⚡Краснодар
18 и 19 июля я буду проводить диагностики в вашем городе!
Для детей от 1.5 до 4.5 лет.
Общая длительность диагностики 60 минут.
🌼 В первой части специалист взаимодействует с ребёнком, с помощью игр и пособий, проводит ряд проб.
🌼 Во второй части родители получают всю информацию о ребёнке в виде обратной связи от специалиста в устной форме.
‼️Задать дополнительные вопросы, узнать стоимость, наличие свобо…
📍Новая точка притяжения нашего города!
В Сочи открылся музей, который представляет собой огромный детализированный макет, где в миниатюре воссозданы сцены из разных эпох - от доисторического периода до наших дней.
Десятки сюжетов, тысячи персонажей и невероятное количество деталей, которые хочется рассматривать снова и снова.
Все это создавалось вручную. Над проектом несколько лет работала команда создателей знамен…
Долгожданный анонс книжных встреч в июле!
Несмотря на сезон отпусков и размеренный летний ритм, продолжаем читать и обсуждать хорошие книги.
В этом месяце встречаемся сразу в двух городах - Сочи и Краснодаре.
Нас ждут две совершенно разные книги.
Если давно хотели присоединиться - июль может стать отличным моментом для этого.
✍🏼Количество мест традиционно ограничено.
📚7 книг до 7 лет
Делюсь своей книжной подборкой.
Уверена, этот список можно дополнять и менять бесконечно. Но мне нравится, что эти книги растут в сложности и шаг за шагом открывают ему мир большой литературы.
#обзор_книг
Однако😅
Хотя на практике это частая история, хорошие вещи часто исчезают гораздо быстрее, чем кажется.
Заканчиваются небольшие тиражи, а издательства не всегда допечатывают книги и пособия. Что-то просто снимают с производства.
Поэтому если вы нашли книгу или пособие, которое действительно хочется использовать с ребёнком, я бы не откладывала.
Пусть лучше оно спокойно ждёт своего времени на полке, чем потом придётся…
❤5🥰2
Showing the 6 most recent of 6 posts we hold for @alesia_vasilevich. 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.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
Елена Лаштабега @elena_lashtabega · 22,838 Telegram ranks this channel #30 of 95 here — alongside 94 others — read 19 September 2026
Екатерина Шрейнер | SchreinerKate | Психолог @schreinerkate_life · 65,333 Telegram ranks this channel #72 of 80 here — alongside 79 others — read 21 August 2026
This channel appears in 2 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 September 2026 — this
entry's latest reading, not the date you are reading this.
“Алеся Василевич” (@alesia_vasilevich), 1,578 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/alesia_vasilevich.
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.