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 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.
Growth
14 measurements spanning 40 days, net +50. 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 1,528–1,612 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
15 Sept 2026, 11:40
1,601
-1
11 Sept 2026, 16:18
1,602
+60
6 Sept 2026, 22:38
1,542
+4
1 Sept 2026, 22:35
1,538
-1
29 Aug 2026, 18:27
1,539
-1
27 Aug 2026, 02:04
1,540
+1
24 Aug 2026, 09:53
1,539
-4
20 Aug 2026, 16:45
1,543
-2
17 Aug 2026, 20:06
1,545
-7
14 Aug 2026, 23:05
1,552
-2
12 Aug 2026, 00:16
1,554
+2
9 Aug 2026, 04:11
1,552
+1
6 Aug 2026, 07:34
1,551
no change
6 Aug 2026, 02:37
1,551
first reading
Engagement
5 posts held, back to 29 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 2 pages 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 5 posts for this entry, the most recent from 6 August 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
85 reactions across 4 posts, in 6 distinct kinds. The most used accounts for 36.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
31
36.5%
❤
30
35.3%
👍
7
8.24%
👏
6
7.06%
💯
6
7.06%
🙏
5
5.88%
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 5 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 111 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 5 most recent posts we hold, published 29 July 2026 to 6 August 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.
💸 Старт продаж курса «Операционный директор девелопера»
На курсе разберете, как выстраивать работу компании через финансовые модели, процессы, метрики и управление командой.
Зачем идти на курс?
🤩 научиться принимать решения о входе в проекты через инвестиционную модель и оценивать их эффективность;
🤩 перевести управление финансами, дебиторкой и подрядчиками из ручного контроля в понятную систему;
🤩 выстроить пр…
🤩 Создаем продукт, о котором все будут говорить
Чтобы ответить на этот вопрос, продуктовый менеджер проходит через пул задач: от выявления потребностей потребителей до изучения конкурентов.
В карточках рассказали, какие компетенции помогают специалисту создать предложение, которое станет самым интересным рынке. А за новыми знаниями, приглашаем на курс «Продуктовый маркетинг в девелопменте».
Как быстро разобраться в новой отрасли 🧐
Выпускница курса «HR в девелопменте» Ольга Ларионова решила проверить новые знания в деле — на реальных задачах и под руководством опытного наставника.
Рассказываем, как стажировка помогает быстрее разобраться в отрасли и усилить свои HR-инструменты.
➖➖➖➖➖➖➖
Если вы хотите научиться применять инструменты в работе, присоединяйтесь к курсу «HR в девелопменте». В программе: пр…
⚡️Как повысить управляемость девелоперской компании
Приглашаем вас на бесплатный вебинар-презентацию нового курса «Операционный директор девелопера».
Спикер — Анна Шишкина, операционный директор Profitbase, эксперт с более чем 15-летним опытом в девелопменте и PropTech:
Анна подробно представит программу курса: расскажет, какие темы вошли в каждый модуль, как организовано обучение, кому подойдет курс и какие резул…
🎯 Бинго риелтора
Если у вас есть друг, который работает в сфере недвижимости, то вы точно знаете, куда его важно пригласить — ДвижениеКонф.
УЧАСТИЕ БЕСПЛАТНОЕ
Showing the 5 most recent of 5 posts we hold for @dvizhenie_school. 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.
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.
Новости Екатеринбурга | Урала @sverdlovskaya_oblasti · 40,384 Telegram ranks this channel #67 of 71 here — alongside 70 others — read 15 September 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list 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 15 September 2026 — this
entry's latest reading, not the date you are reading this.
“Движение | школа недвижимости” (@dvizhenie_school), 1,601 subscribers as measured 15 September 2026. Telegram Register, tgregister.com/channel/dvizhenie_school.
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.