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 11 August 2026 and assigned it the closest of 31 fixed categories, at 97% 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.
Views per post sit far below this size band
20.4 average views per post against 69,812 subscribers — an engagement rate of 0.029%. Across the 23,944 registered channels in the same cohort — 31,623–99,992 subscribers — the middle half sit between 2.65% and 14.9%, with a median of 6.76%.
What this was computed from
Window
30 days (17 September 2026 – 17 October 2026)
Posts measured
39 of 39 published in the window (39 exact, 0 rounded by Telegram)
Views totalled
796
Mature posts only
0.034% over 32 posts read at least 24h after publication
When this is recorded. A channel is listed here only when its engagement rate sits at or below the 1st percentile of its cohort and is at least 3× away from that cohort’s median — below it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal. A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the key err_low, last confirmed 17 October 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.
Growth
40 measurements spanning 69 days, net -5,237. 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 69,026–75,835 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 40
Measured (UTC)
Subscribers
Change
17 Oct 2026, 12:56
69,812
-3
16 Oct 2026, 13:21
69,815
-1,089
15 Oct 2026, 13:15
70,904
-6
14 Oct 2026, 14:06
70,910
-7
13 Oct 2026, 04:39
70,917
-610
8 Oct 2026, 21:22
71,527
-626
4 Oct 2026, 07:37
72,153
-925
25 Sept 2026, 12:59
73,078
-17
19 Sept 2026, 04:17
73,095
-10
16 Sept 2026, 21:57
73,105
-11
14 Sept 2026, 20:58
73,116
-4
13 Sept 2026, 07:37
73,120
-8
11 Sept 2026, 13:02
73,128
-22
8 Sept 2026, 17:55
73,150
-768
5 Sept 2026, 14:38
73,918
-22
3 Sept 2026, 13:38
73,940
-15
2 Sept 2026, 08:48
73,955
-37
1 Sept 2026, 09:13
73,992
-70
31 Aug 2026, 08:13
74,062
-28
30 Aug 2026, 11:15
74,090
first reading
Engagement
282 posts held, back to 8 August 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 138 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
0.029%
avg views ÷ 69,812 subscribers
Avg views / post
20.4
39 posts measured
Reaction rate
1.25%
reactions ÷ views · ER floor
Posts in window
39
of 282 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. It is computed over the 3 of 39 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 2 October 2026
Posts held
282 (8 August 2026 – 2 October 2026)
Views total
796
Reactions total
1
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
17 Oct 2026, 16:56 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
≈1,730
Videos
≈242
Links
≈285
Lifetime counters from Telegram’s own channel header, read 17 October 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
3h 13m
Average length
5m 52s
Measured directly from 33 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
84 reactions across 46 posts, in 27 distinct kinds. The most used accounts for 14.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
12
14.3%
😢
5
5.95%
🤩
5
5.95%
🥰
5
5.95%
👎
4
4.76%
👻
4
4.76%
😁
4
4.76%
😎
4
4.76%
⚡
3
3.57%
❤
3
3.57%
👍
3
3.57%
💯
3
3.57%
🙏
3
3.57%
🤓
3
3.57%
🤣
3
3.57%
🎉
2
2.38%
👌
2
2.38%
😇
2
2.38%
😍
2
2.38%
😘
2
2.38%
7 further kinds
10
11.9%
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 48 of the 282 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 84 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 282 most recent posts we hold, published 8 August 2026 to 2 October 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.
Deutschland erreicht unter Schwarz-Rot die höchste Staatsquote seit 1960 und liegt dabei noch über der der Corona-Zeit. Die Abgabenquote liegt nach BMF bei 39,4 % auf Rekord-Niveau. Also höher als unter der Ampel oder Rotgrün. Wer sozialistische Politik will, der braucht nicht die LINKE wählen, der ist mit Bundeskanzler Friedrich Merz gut bedient.
Hape Kerkeling als „Experte“ zum AfD Verbotsverfahren. Dann sollte man auch noch Dieter Hallervorden, Dieter Nuhr, Harald Schmidt und Lisa Eckhart zu Rate ziehen. Zwischen den Komikern und den „Experten“, Aktivisten und Politikern der Altparteien gibt es in dieser Frage ohnehin kaum noch einen sichtbaren Unterschied. Ihr macht Euch lächerlich.
Familienministerin Prien droht Sachsen-Anhalt für den Fall, dass die AfD-Regierung dort die Lehrpläne verändern. Das ist das Demokratie-Verständnis der CDU. Die AfD hat einen Erdrutschsieg in Sachsen-Anhalt erreicht, Bildungspolitik ist klar Ländersache. Die Bürger haben dort auch eine andere Bildungspolitik gewählt, ohne Gender-Gaga und Frühsexualisierung, und die CDU-Ministerin bedroht die Bürger damit, dass ihre B…
„Vielmehr habe sie den Eindruck, „dass die Befürworter eines Verbots der AfD darauf abzielen, die AfD als unwillkommenen Konkurrenten auszuschalten“. Zu diesem Zweck würden sie „auch die inländischen Nachrichtendienste instrumentalisieren, während diese Behörden ihrerseits in problematischer Weise politische Agitation gegen die AfD betreiben.“
(…)
„Die Fraktion Die Linke habe das Auswärtige Amt, den Landtagspräside…
💥SPD LANDESVORSTAND BESCHLIESST EINSTIMMIG!💥
Der Berliner SPD-Landesvorstand hat am Samstag einstimmig für Sondierungsgespräche mit Linken und Grünen gestimmt. Damit haben nun alle drei Parteien Gesprächen über eine mögliche rot-grün-rote Regierung zugestimmt.
SPD-Landeschef Steffen Krach hatte selbst noch wenige Tage zuvor hohe Hürden für eine Zusammenarbeit mit der Linken formuliert. Die Debatten der vergangenen …
Von Bielefeld bei Maximilian Kneller nach Mönchengladbach zu Dr. Christian Wirth: Danke für die Einladung! Auch an die Kollegen Christian Zaum, Jochen Haug, Hauke Finger, Kay Gottschalk unserer NRW-Landesgruppe im Bundestag. Was für ein schöner Ort, an dem wir da waren und der dann leider doch nicht geheim blieb. Die linke Dullitruppe hat also wieder versucht, alles zu verhindern, wodurch ich meine erste echte Polize…
Ein (Oktober)Fest mit und bei Anna Rathert in Recklinghausen. Es war großartig. Leider musste ich vor dem gemütlichen Teil schon weiter. Aber statt mit netten Menschen bei guter Musik und interessanten Gesprächen- … also, das Bordbistro der Deutschen Bahn ist auch sehr zu empfehlen 😉
Ich glaubte, ich sei in Istanbul. Aber es war wohl doch Bielefeld. Auch deswegen machen wir das. Wegen des Stadtbildes. Danke an Kneller, Dr. Florian Sander und die Stadtratsfraktion. Es war mir ein großes Vergnügen.
Showing the 12 most recent of 282 posts we hold for @Beatrixvon_storch0. 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.
Mentions
Names
Channels on the register whose handles appear in this channel's posts.
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.
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 October 2026 — this
entry's latest reading, not the date you are reading this.
“Beatrix von Storch” (@Beatrixvon_storch0), 69,812 subscribers as measured 17 October 2026. Telegram Register, tgregister.com/channel/Beatrixvon_storch0.
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.