Politics & activism — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 42% 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
32 measurements spanning 43 days, net -257. 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 15,968–16,303 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 32
Measured (UTC)
Subscribers
Change
18 Sept 2026, 18:40
16,007
-15
16 Sept 2026, 07:02
16,022
-4
14 Sept 2026, 16:40
16,026
-20
12 Sept 2026, 23:56
16,046
-9
10 Sept 2026, 21:38
16,055
-18
7 Sept 2026, 21:19
16,073
-14
4 Sept 2026, 19:22
16,087
-10
3 Sept 2026, 01:54
16,097
-6
1 Sept 2026, 21:48
16,103
-7
31 Aug 2026, 23:57
16,110
-11
30 Aug 2026, 20:08
16,121
-3
29 Aug 2026, 21:04
16,124
-5
28 Aug 2026, 20:42
16,129
-7
27 Aug 2026, 22:13
16,136
-8
26 Aug 2026, 00:55
16,144
-2
25 Aug 2026, 04:03
16,146
-1
23 Aug 2026, 21:29
16,147
-8
22 Aug 2026, 04:05
16,155
-10
20 Aug 2026, 20:12
16,165
-3
19 Aug 2026, 23:37
16,168
first reading
Engagement
28 posts held, back to 9 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 54 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
9.21%
avg views ÷ 16,007 subscribers
Avg views / post
1,480
5 posts measured
Reaction rate
2.14%
reactions ÷ views · ER floor
Posts in window
5
of 28 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 2 September 2026
Posts held
28 (9 June 2026 – 2 September 2026)
Views total
7,375
Reactions total
158
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Sept 2026, 10:09 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
28m 14s
Average length
1m 14s
Measured directly from 23 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
1,470 reactions across 28 posts, in 27 distinct kinds. The most used accounts for 17.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
😈
261
17.8%
❤
244
16.6%
🤮
197
13.4%
🤬
153
10.4%
👍
147
10.0%
🔥
102
6.94%
👏
95
6.46%
🙏
60
4.08%
😁
58
3.95%
😢
31
2.11%
🖕
24
1.63%
✍
21
1.43%
💩
13
0.884%
🤡
13
0.884%
🥰
9
0.612%
💊
7
0.476%
😨
6
0.408%
🤔
6
0.408%
😎
5
0.34%
🤷♂
4
0.272%
7 further kinds
14
0.952%
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 28 of the 28 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 1,470 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 28 most recent posts we hold, published 9 June 2026 to 2 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.
💉☠️
Incontáveis pessoas que morreram por causa das vacinas contra a Covid foram contadas como mortes de “não vacinados”.
Como?
“A definição de estar vacinado era duas a três semanas após a sua segunda dose.”
Jeffrey Tucker acabou de expor como os dados da Covid foram manipulados. #fraudemia
#despertatuquedormes #redpill #saiadamatrix #saude
https://x.com/brownstoneinst/status/2093063148647428130?s=20
🔄 Compar…
💉💔
As injeções de mRNA da COVID-19 podem causar a SÍNDROME DE MORTE ADULTA SÚBITA (SADS) anos após a injeção, ao danificar permanentemente o coração com micro-cicatrizes letais.
6 estudos revisados por pares mostram que a miocardite induzida por vacinas NÃO é "leve e transitória", mas FATAL.
#saude #despertatuquedormes #saiadamatrix #redpill #desperta
🔄 Compartilhe 👇🏻
👉🏻 No Instagram
👉🏻 No Facebook
👉🏻 No Twi…
Off
Em 2021, Luc Montagnier, vencedor do Nobel de Fisiologia ou Medicina de 2008 pela descoberta do HIV, já falava publicamente sobre a relação entre vacinação contra a Covid-19, príons e doença de Creutzfeldt-Jakob.
Meses depois, em janeiro de 2022, ele voltou ao tema durante um debate na Câmara dos Deputados de Luxemburgo, onde sua preocupação ficou registrada oficialmente.
O vídeo e o print incluído neste post …
💉❌️ Ensaio Clínico de “Vacina” Anticâncer de mRNA da BioNTech INTERROMPIDO Devido a Sinal Alarmante de Mortalidade
O Conselho Independente de Monitoramento d Segurança de Dados sinalizou um desequilíbrio na sobrevida geral após vítimas d câncer receberem um regime agressivo d hiperdosagem de até 15 doses IV de mRNA.
A BioNTech NÃO divulgou a direção do desequilíbrio d mortalidade ou as contagens de mortes em cada b…
🚨
"As "vacinas" COVID causaram uma pandemia real de todos os tipos de doenças e mortes súbitas"...
"Sabemos que as injeções têm um efeito negativo, promovem a doença e a morte"...
"Não salvaram nem uma única vida..."
🇨🇭 Dr. Thomas Binder, Cardiologista.
#saude #saiadamatrix #despertatuquedormes #redpill #desperta
◇ Compartilhe 👇🏻
👉🏻 No Instagram
👉🏻 No Facebook
👉🏻 No Twitter-X
Telegram 👇🏻 siga 👇🏻
T.me/des
⚠️ BILL GATES DISSE QUE A PRÓXIMA PANDEMIA ESTÁ CHEGANDO — E SERÁ PIOR QUE A COVID
“A COVID matou milhões. Foi horrível. Conseguimos a vacina… mas a próxima pode ser muito mais grave.”
Ele vem “prevendo” pandemias há mais de uma década enquanto sua fundação despeja bilhões em vacinas, vigilância e “preparação”.
Todas as vezes que ele abre a boca sobre o próximo surto mortal, o mundo deveria estar perguntando:
Por …
📡⚡️🛰
H.A.A.R.P - “A tecnologia existe. As patentes existem. As correlações existem.”
ARMA DE GEOENGENHARIA E GEOFÍSICA ativa na ionosfera que promove o que for preciso no clima em pontos específico da terra.
#saiadamatrix #redpill #desperta #despertem #wakeup
》COMPARTILHE 👇🏻
👉🏻 Instagram
👉🏻 Facebook
👉🏻 Twitter-X
Siga 👇🏻 aqui no telegram
T.me/despertandoleoes
💉🤧🤒
O FDA aprovou a 💉 da gripe de mRNA da Moderna, apesar de ela causar 294% MAIS REAÇÕES SISTÊMICAS GRAVES do que a já perigosa vacina tradicional de gripe.
Os receptores da vacina de gripe de mRNA sofreram uma TAXA DE REAÇÃO ADVERSA de 75,3%, e não houve grupo placebo no ensaio. #saude
https://x.com/NicHulscher/status/2087579645239583069?s=20
#despertatuquedormes #redpill #saiadamatrix #desperta
● Compartilhe 👇…
🎖✨️🎖✨️🎖✨️🎖✨️🎖✨️
Parabéns a você que não tomou a picada e permaneceu firme e forte contra as ciladas da fraudemia. #wakeup
#saiadamatrix #redpill #despertem #desperta
● Compartilhe 👇🏻 com alguém
👉🏻 Instagram
👉🏻 Facebook
👉🏻 Twitter-X
Telegram 👇🏻
T.me/despertandoleoes
🤡 Quem lembra do Kim Kataguiri apoiando passaporte de vacina pra entrar em lugares? #tosco
#fraudemia #saiadamatrix #despertatuquedormes #redpill
● Compartilhe 👇🏻
👉🏻 Instagram
👉🏻 Facebook
👉🏻 Twitter/X
Telegram 👇🏻
T.me/despertandoleoes
🤬40🤮33😈5💩1🖕1
Signed Daniel Cabral
Showing the 12 most recent of 28 posts we hold for @despertandoleoes. 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
Republishes
Channels on the register whose posts this channel has forwarded.
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.
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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“Despertando Leões 🦁💥” (@despertandoleoes), 16,007 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/despertandoleoes.
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.