Politics & activism — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 8 August 2026 and assigned it the closest of 31 fixed categories, at 99% 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.
Content that also appears on other registered channels
Posts published here appear word for word on 1 other registered channel. They sit inside a group of 377 channels that share the same post bodies with each other. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (3 of the pairs behind the counts below)
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 5 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 2,385 comparable posts for this entry, running 28 March 2020 to 6 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Across the whole group of 377, the earliest publisher we hold is @mash. That is a statement about our reading window, not a claim of authorship.
Views and reactions moved apart
On 3 of the 3 posts we watched over 30days, the view counter climbed while the reaction counter stayed where it was — by more than this channel’s own reactions-per-view rate can account for. That rate, measured on this entry, is 0.0249 reactions per view.
Each interval, as we read it — views and reactions before and after
Expectedis the view gain multiplied by this channel’s own prior reactions-per-view rate over the same post — not a corpus average, so a channel whose audience never reacts is compared only against itself. Every interval is credited in the direction that makes the observation harder to record, never easier: t.me renders views and reactions to three significant figures above ~1,000, so a raw delta can be a rendering step. Every delta below is at least 4 x the coarser reading's step, the view gain is discounted by a full step and the reaction gain credited with one. Measured by tgregister velocity.py (our own t.me/s/ readings).
What this does and does not say.It says the two counters moved apart, by more than rounding and more than this channel’s own history predicts. It asserts no cause. Views arriving from outside Telegram, an embedded or forwarded copy of the post, and a burst of readers who simply do not react all produce this shape. This detector has recorded very few observations across the whole register, and its precision has not been measured; treat it as an anomaly worth looking at, not as a finding.
Recorded under the keys clone_mutual · view_reaction_decoupling, last confirmed 12 August 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.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 376 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
326 more channels are in this same group but not listed individually here.
Growth
8 measurements spanning 7 days, net +5,387. 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 1,312,836–1,331,182 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
12 Aug 2026, 14:24
1,324,056
-387
11 Aug 2026, 17:02
1,324,443
-4,622
10 Aug 2026, 19:18
1,329,065
+14,112
9 Aug 2026, 19:04
1,314,953
-4,880
8 Aug 2026, 21:31
1,319,833
-6,241
7 Aug 2026, 19:54
1,326,074
+2,905
6 Aug 2026, 18:10
1,323,169
+4,500
6 Aug 2026, 00:41
1,318,669
first reading
Engagement
2,540 posts held, back to 27 March 2020 — the reader has reached the start of this channel’s public history, so this is the full archive Telegram still exposes. Read across 229 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
32.8%
avg views ÷ 1,324,056 subscribers
Avg views / post
435,000
25 posts measured
Reaction rate
1.88%
reactions ÷ views · ER floor
Posts in window
25
of 2,540 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 12 August 2026
Posts held
2,540 (27 March 2020 – 12 August 2026)
Views total
10,872,500
Reactions total
204,751
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
12 Aug 2026, 23:30 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
Photos
≈2,810
Videos
≈197
Links
≈812
Lifetime counters from Telegram’s own channel header, read 12 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
0s
Average length
0s
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.
View velocity
How fast this channel’s own posts pick up views, from re-reading them repeatedly in the hours and days after they were published rather than the single reading most entries on this register get. Coverage is early and only a small minority of channels hold it at all — a gap in this section means the post has not been re-read again yet, not that nothing happened.
3 most recently posted, with a view-velocity reading
Curve is every standard checkpoint we hold a reading for (+1h, +3h, +6h, +12h, +24h, +48h, +7d after posting) — measured where a real reading landed close enough to that age, interpolated where it did not but readings on both sides let one be worked out between them. Nothing is ever extrapolated past the last real reading. Latest reading is the newest view and reaction count we hold for the post, side by side, so a gap between how views and reactions moved is visible without following it into the Observations section above. 24h reach is that one checkpoint on its own, labelled the same way. Half of last-observed viewsis the age at which a post’s view count crossed half of the highest figure we have read for it so far — an upper bound when the very first reading was already past half (we cannot see the actual crossing), and biased low while the post is still climbing, since “half of final” is dividing by a number that has not finished growing yet. Both caveats are printed inline wherever they apply, never silently dropped.
Reaction mix
174,040 reactions across 21 posts, in 18 distinct kinds. The most used accounts for 59.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
102,629
59.0%
❤
16,568
9.52%
👏
16,249
9.34%
🔥
16,225
9.32%
🤬
10,848
6.23%
👎
10,734
6.17%
💯
421
0.242%
🙏
200
0.115%
❤🔥
56
0.032%
🤔
23
0.013%
🌚
22
0.013%
🫡
22
0.013%
🤝
18
0.01%
✍
9
0.005%
😱
6
0.003%
🥰
6
0.003%
😢
3
0.002%
💔
1
0.001%
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 1,000 of the 1,000 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 19,892,434reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 1,000 most recent posts we hold (the sample is capped at 1,000), published 10 September 2024 to 12 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.
Telegram Stars
Stars received
15
across the posts below
Posts paid on
10
of 1,000 we hold a reading for · 1%
Most on one post
2
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @kvmalofeev. 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 1,000 most recent posts we hold for this entry (the sample is capped at 1,000), published 10 September 2024 to 12 August 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.
Русский демографический прорыв возможен. Нужна только твёрдая государственная воля.
Программа "Нижегородский миллион" всего за 10 месяцев увеличила суммарный коэффициент рождаемости в регионе более чем на 6% (до 1,358 ребёнка на женщину). Регион обогнал средние показатели по всей России (1,344) и тем более по Приволжскому округу (1,292).
В объявленное губернатором Глебом Никитиным "Пятилетие семьи" (2025–2030) к ре…
Сервис "Шедеврум" от "Яндекса" на запрос нарисовать русскую семью в виде родителей выдаёт однополых извращенцев. А нарисовать государственный флаг России вообще не может: "не знает" его цвета и их порядок.
Очевидно, это не случайная техническая ошибка, а наглядное свидетельство того, как IT-гигант формирует смыслы. Когда формально отечественная нейросеть выдаёт содомитские мерзости и глумится над государственными си…
Власти Петербурга намерены продлить до конца 2027 года запрет на работу мигрантов в такси и сервисах доставки. Сейчас он действует до конца декабря. Эффект стал понятен ещё в мае – тогда губернатор Беглов заявил о снижении преступности среди иностранцев на 28,3%.
Два интересных момента. Первый – на треть снизилось число преступлений и против самих мигрантов. Второй – местные силовики предложили расширить запрет на р…
Сергей Лавров выступил за возвращение своему родному подмосковному Ногинску его исторического имени Богородск.
Полностью поддерживаю прекрасную инициативу Сергея Викторовича. Возрождение России с тысячелетней историей невозможно без возвращения нашим городам и весям, улицам и площадям исторических названий. Если мы не будем чтить память наших предков, то почему наши потомки должны будут помнить нас?
Богородск стал …
Вражеская разведка сообщила, что КНДР начала переброску в западную часть России ракетного подразделения. Оно может быть оснащено 120 баллистическими ракетами и шестью пусковыми установками.
Хорошо бы, если так. Корейские союзники словом и делом доказали, что благодарны России за многолетнюю помощь. Уже в 2022 году КНДР поставила нам миллионы снарядов и ракет ближнего радиуса действия. Наши бойцы использовали стрелко…
О ЗОЛОТОМ МИЛЛИАРДЕ
Приоткрывается ещё одно окно Овертона. Группа малоизвестных учёных из разных уголков мира пришла к выводу, что население Земли нужно сократить до 4 миллиардов к 2200 году. Для этого глобальный коэффициент рождаемости предлагается снизить до 1,75. А то у Земли слишком быстро истощаются ресурсы.
Нам предлагают сделать первый добровольный шаг к вымиранию. Новые мальтузианцы – Билл Гейтс, принц Гарр…
О ПЕРЕГОВОРАХ
Трамп, Вэнс и Рубио по очереди высказались о том, что дальнейшее усиление ударов по России должно подтолкнуть нас к переговорам о мире:
Трамп: Удары по российским объектам – это эскалация. Но это эскалация, которая может привести к прекращению конфликта.
Вэнс: Изматывание России без контрнаступления Украины вполне может создать пространство, необходимое нам для завершения этого дела.
Рубио: Украина …
Нас подводят к мысли о том, что ИИ сможет управлять государством. Он якобы беспристрастен, мудр и лишён страстей. Это не просто ложь – это прямой путь к технофашизму.
Сегодня – День ВДВ, "Войск дяди Васи", легендарного генерала Маргелова. Герой Великой Отечественной войны, освободитель Николаева и Одессы, он заложил в десантниках традицию побеждать, которую они хранят и на нынешней войне.
Символично и промыслительно, что День основания ВДВ совпал с Днём Пророка Илии – вознесённого Господом на Небо на огненной колеснице, а потому ставшего Небесным покровителем десантуры.
С Днём П…
В день Преподобного Серафима Саровского Святейший Патриарх Кирилл напомнил, что создание ядерного оружия в Сарове было Божественным замыслом:
Вот таким образом, через труд учёных, инженеров, рабочих... несомненно, явилась благодать и милость Божия над страной нашей.
Промысл Божий о России, Третьем Риме, поистине удивителен. Неслучайно именно Серафим Саровский, чьё имя переводится на русский как "Пламенный" или "Пыл…
О ВЫДВОРЕНИИ
За нарушение законов России в первом полугодии выдворили 43 700 мигрантов. На 65% больше, чем годом ранее. Эффективность предоставления МВД полномочий выдворять во внесудебном порядке налицо.
Сейчас перечень оснований для выдворения расширен с 22 до 45 пунктов – добавлены нарушения миграционного режима, мелкое хулиганство, дискредитация армии и многое другое. Число выгнанных иностранцев, скорее всего, …
Кузбасс – шахтёрский край сильных духом людей. С большой радостью открыли здесь региональный "Клуб 2050".
Коллеги уже приступили к работе над нашим научным докладом "Россия 2050. 25 лет: вперёд или назад?", но задачи клуба гораздо шире. Это и формирование образа Русского будущего, и глубокий анализ внешних и внутренних угроз, и поиск ответов на них. Но самое главное – мобилизация интеллектуального потенциала региона…
👍3,920❤919👏890🔥859👎204🤬187🙏10❤🔥5
Showing the 12 most recent of 2,540 posts we hold for @kvmalofeev. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Citation-graph rank
Citation-graph rank — 3,496 of 1,151,006entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
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 52 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
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.
Handles this channel named that no longer answer
Dead references
3
handles named in this channel’s posts, vacant today
Evidenced gone
2
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@kvmalofeev named 3 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all.A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Evidenced gone
We ourselves saw each of these resolve to a real page at some point before it went vacant — a genuine, evidenced change, not an inference from absence.
@tsargradtv named in 51 posts, 8 August 2026 – 8 August 2026 · confirmed gone 10 August 2026 (two independent sightings — see how we confirm a dead handle)evidenced
@mnogonazi named in 1 post, 8 August 2026 – 8 August 2026 · confirmed gone 11 August 2026 (two independent sightings — see how we confirm a dead handle)evidenced
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@rt_russian named in 1 post, 8 August 2026 – 8 August 2026
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s.When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 9 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
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.
عجیب ولی واقعی @ajibvalivaghaei · 577,266 Telegram ranks this channel #73 of 75 here — alongside 74 others — read 9 August 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.
Domains linked from posts
10 domainsthis channel’s own posts have linked to, measured by scanning the post bodies themselves — not the channel’s description, which is the separate Declared links section below when this entry has one. Appearing here is not a claim about who runs the linked site or why the channel linked to it; an advertisement, a news citation and a malicious link all leave the same kind of row.
A Wikidata item names this Telegram handle as belonging to the entity it describes. This is Wikidata’s claim, not a verification made by this register — nobody here confirmed that the account is genuinely operated by the entity named. Wikidata content is CC0; every fact below is dated to when it was read from Wikidata, not to when the association was first made there.
This handle named by sources this register does not control and did not measure — each shown exactly as found, attributed by name, dated to when it was read.
Hacker News
This handle was named once in a Hacker News comment or story, via the public Algolia search API. HN comment and story text has no confirmed reuse licence, so nothing quoted from either is reproduced here — only that a mention exists, when, and by whom, with a link to read it at the source.
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 12 August 2026 — this
entry's latest reading, not the date you are reading this.
“Константин Малофеев” (@kvmalofeev), 1,324,056 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/kvmalofeev.
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.
