Education β a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channelβs own recent posts on 4 October 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a modelβs 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 β 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
9 measurements spanning 56 days, net -4. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between β snapshots are recorded only when a count changes, so gaps mean βno change observedβ, never βinterpolatedβ. The vertical axis spans 215β248 and does not start at zero.
Measurement log β every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
3 Nov 2026, 19:37
219
-1
28 Oct 2026, 16:41
220
-5
21 Oct 2026, 00:17
225
-4
14 Oct 2026, 01:31
229
-11
4 Oct 2026, 10:18
240
-4
19 Sept 2026, 00:18
244
+24
11 Sept 2026, 11:58
220
-3
9 Sept 2026, 00:22
223
no change
8 Sept 2026, 23:47
223
first reading
Engagement
20 posts held, back to 1 November 2025 β the reader has not yet reached the start of this channelβs public history, so older posts may sit further back, unread. Read across 1 page of Telegramβs 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 β we hold 20 posts for this entry, the most recent from 7 September 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
3m 27s
Average length
1m 09s
Measured directly from 3 videos with a duration reading, out of the posts we hold for this channel β not this channelβs 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 Telegramβs own rounded chrome, so it carries no β mark.
Reaction mix
106 reactions across 17 posts, in 9 distinct kinds. The most used accounts for 43.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
β€
46
43.4%
π₯
20
18.9%
π
15
14.2%
β€βπ₯
7
6.60%
π
6
5.66%
π
5
4.72%
π₯°
5
4.72%
customΒ 5312358509126373704
1
0.943%
customΒ 5337223440602517391
1
0.943%
Custom emoji. 2 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id β no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them are Telegramβs.
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 β π is thanks in one channel and mourning in another β 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 β 4.34K, 1.2M β 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 17 of the 20 sampled posts in this sample. Summed by Telegramβs own count on each post β not by adding up the per-emoji breakdown above β those same posts carry 106 reactions in total: the kind of figure the paragraph above means by βa reaction total printed elsewhere on the pageβ.
Measured over the 20 most recent posts we hold, published 1 November 2025 to 7 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.
π₯ MULTILEVEL OCTOBER β 1 OYLIK INTENSIV KURS
π Multilevel imtihoniga tayyorgarlik koβrmoqchimisiz?
Unda siz uchun maxsus ishlab chiqilgan 1 oylik Multilevel kursimizga qabul boshlandi!
π KURS HAQIDA
πΉ Boshlanish sanasi: 15-sentabr
πΉ Davomiyligi: 1 oy
πΉ Dars vaqti: 20:30
πΉ Format: Telegram Stream
πΉ Haftada: 3 kun jonli dars
πΉ Har kuni video darslar + vazifalar
πΉ C1 darajadagi mentor nazorati
πΉ Speaking Mock & Writiβ¦
Keling ungacha reading part 1 ishlaymiz
Multilevel imtihonida tushgan Reading Part 1
The bear can be a dangerous animal. The adult (1)β¦β¦..is very strong and it can kill a person. Bears are good at climbing trees and they can run very fast. Bears can (2)β¦β¦......, as fast as people. But they cannot see well and,like most animals, they find food by using their noses. There are seven kinds of bears. The largest is theβ¦
PART 3 UCHUN READY-MADE PHRASES
Fikr bildirish
β’ I would say thatβ¦ β Menimchaβ¦
β’ From my perspective,β¦ β Mening nuqtayi nazarimdanβ¦
β’ I tend to believe thatβ¦ β Men β¦ deb hisoblashga moyilman.
β’ It largely depends onβ¦ β Bu asosan β¦ga bogβliq.
Sabab berish
β’ The main reason is thatβ¦ β Asosiy sabab shukiβ¦
β’ This is mainly becauseβ¦ β Bu asosan shuning uchunkiβ¦
β’ One possible explanation isβ¦ β Buning mumkin boβlgan saβ¦
Showing the 12 most recent of 20 posts we hold for @Multilevel_with_LinguaSayyora. 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 β was rounded by Telegram before we ever saw it β t.me prints views in full below 1,000 and to three significant figures above, so β1,200,000 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 1 registered channel β 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 β that handle may belong to someone else now, and crediting todayβs namer to yesterdayβs 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 β 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 β the βNamed by N registered channelsβ 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 3 November 2026 β this
entry's latest reading, not the date you are reading this.
βπ΄πππππππππ ππππ π³πππππ πΊππππππβ (@Multilevel_with_LinguaSayyora), 219 subscribers as measured 3 November 2026. Telegram Register, tgregister.com/channel/Multilevel_with_LinguaSayyora.
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 Β· 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.
