Other / unclassifiable — 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 the other topics.
Growth
61 measurements spanning 98 days, net -198. 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 13,779–14,037 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 61
Measured (UTC)
Subscribers
Change
12 Nov 2026, 14:47
13,809
-10
10 Nov 2026, 10:11
13,819
+1
8 Nov 2026, 23:37
13,818
-5
7 Nov 2026, 13:21
13,823
-5
6 Nov 2026, 15:15
13,828
-3
5 Nov 2026, 12:36
13,831
+2
4 Nov 2026, 12:35
13,829
-4
3 Nov 2026, 14:28
13,833
-3
2 Nov 2026, 12:19
13,836
-7
1 Nov 2026, 09:56
13,843
-3
31 Oct 2026, 09:55
13,846
-7
30 Oct 2026, 07:54
13,853
-3
28 Oct 2026, 10:40
13,856
-1
27 Oct 2026, 11:37
13,857
-1
26 Oct 2026, 09:31
13,858
+4
25 Oct 2026, 09:00
13,854
-1
24 Oct 2026, 07:50
13,855
-1
23 Oct 2026, 07:05
13,856
-2
22 Oct 2026, 05:46
13,858
-7
21 Oct 2026, 02:18
13,865
first reading
Engagement
104 posts held, back to 27 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 73 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
9.09%
avg views ÷ 13,809 subscribers
Avg views / post
1,250
49 posts measured
Reaction rate
2.14%
reactions ÷ views · ER floor
Posts in window
50
of 104 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 48 of 49 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 14 November 2026
Posts held
104 (27 July 2026 – 14 November 2026)
Views total
61,490
Reactions total
1,309
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
14 Nov 2026, 08:21 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
≈2,500
Videos
≈1,330
Links
≈9,350
Lifetime counters from Telegram’s own channel header, read 14 November 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
9m 04s
Average length
2m 16s
Measured directly from 4 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
2,677 reactions across 102 posts, in 5 distinct kinds. The most used accounts for 39.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,056
39.4%
👍
1,037
38.7%
💯
285
10.6%
👏
211
7.88%
🤝
88
3.29%
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 102 of the 104 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 2,677 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 104 most recent posts we hold, published 27 July 2026 to 14 November 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.
Recent posts
Telegram’s own ‘edited’ marker: 4 of 50 posts held from the last 30 days (8.00%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
🆕
Viele beschäftigen sich seit Jahren mit Chlordioxid.
Und genau das ist manchmal das Problem.
Denn wer sich jahrelang in denselben Gruppen, denselben Kanälen, denselben Büchern und denselben Erzählungen bewegt, merkt oft nicht mehr, dass er sich nicht weiterentwickelt.
Er bewegt sich im Kreis.
Immer dieselben Protokolle.
Immer dieselben Namen.
Immer dieselben Versprechen.
Immer dieselben Abwehrreflexe, sobald jem…
Für Anfragen und Informationen zu meinen Veröffentlichungen erreichen Sie mich telefonisch unter:
+49 (0) 5536 23 530 56
Vertiefende Inhalte, Analysen und Einordnungen finden Sie hier:
Medizinjournalistische Webseite
https://www.rainer-taufertshoefer-medizinjournalist.de
Forschungsseminare – zentraler Informationspool
https://www.forschungsseminare.de
Social Media & laufende Kommentare
Telegram (öffentlich)
…
MEDIZIN IM ALLTAG
DREI PARANÜSSE – UND DER VERHÄNGNISVOLLE RECHENFEHLER
Wenn drei gesunde Empfehlungen zusammen plötzlich zum Problem werden.
Stellen Sie sich eine Frau vor, die beschlossen hat, ihre Gesundheit endlich selbst in die Hand zu nehmen.
Nach Jahren enttäuschender Erfahrungen mit verschiedenen Behandlungen hat sie das Vertrauen verloren, dass sich jemand wirklich mit den Zusammenhängen ihrer Beschwerde…
𝗥𝗲𝗶𝗰𝗵𝗲𝗹𝘁 𝗴𝗲𝗴𝗲𝗻 𝗥𝗲𝗶𝗰𝗵𝗲𝗹𝘁
„Man darf natürlich schneiden und verkürzen, man darf nur den Sinn nicht entstellen.“ Das sagt Julian Reichelt selbst, im selben Gespräch, aus dem dieses Video stammt. Daran lasse ich mich gern messen. Ich habe nichts entstellt. Ich habe nur nebeneinandergestellt.
𝗗𝗮𝗺𝗮𝗹𝘀
Der erste Ausschnitt stammt aus der Corona-Zeit, Originalquelle und Datum sind unbekannt. Reichelt nennt den Impfstoff da…
MEDIZIN IM ALLTAG
Die Schilddrüsentablette wirkte nicht mehr wie erwartet – obwohl die Dosis unverändert blieb
Drei Nahrungsergänzungsmittel, ein Schilddrüsenhormon und ein Einnahmefehler mit möglichen Folgen.
Stellen Sie sich eine Frau vor, die seit Jahren wegen einer Schilddrüsenunterfunktion Levothyroxin einnimmt. Ihre Dosis ist unverändert. Zusätzlich verfolgt sie Ernährungskanäle auf YouTube und beginnt, Nahr…
#Krisenvorsorge
𝗗𝗿𝗲𝗶 𝗪𝗼𝗰𝗵𝗲𝗻 𝗗𝘂𝗻𝗸𝗲𝗹𝗵𝗲𝗶𝘁. 𝗘𝗶𝗻 𝗦𝘇𝗲𝗻𝗮𝗿𝗶𝗼 𝘃𝗼𝗻 𝘃𝗶𝗲𝗹𝗲𝗻.
𝗧𝗲𝗶𝗹 𝟮 𝘃𝗼𝗻 𝟮
Man stelle sich vor, die Brandts würden in der zweiten Woche immer noch in jener Turnhalle sitzen, zwischen zweihundert fremden Menschen auf Feldbetten, mit einer Wasserausgabe, vor der sich jeden Morgen eine Schlange bildet, und ohne zu wissen, wie es ihrem Haus geht. Man stelle sich vor, das Pflegeheim zwei Straßen weiter würde evakuier…
#Krisenvorsorge
𝗗𝗿𝗲𝗶 𝗪𝗼𝗰𝗵𝗲𝗻 𝗗𝘂𝗻𝗸𝗲𝗹𝗵𝗲𝗶𝘁. 𝗘𝗶𝗻 𝗦𝘇𝗲𝗻𝗮𝗿𝗶𝗼 𝘃𝗼𝗻 𝘃𝗶𝗲𝗹𝗲𝗻.
𝗧𝗲𝗶𝗹 𝟭 𝘃𝗼𝗻 𝟮
Blackout, Sabotage, Cyberangriffe, die Drohkulisse eines Krieges mit Russland: Kaum ein Thema ist im Moment so präsent, und kaum eines wird so abstrakt besprochen. Was folgt, ist ein fiktives Extremszenario, die Familie und der Ablauf sind erfunden. Es ist ein Beispiel von vielen, die sich so oder ähnlich in jeder Region Deutschlands absp…
𝗪𝗵𝗶𝘀𝘁𝗹𝗲𝗯𝗹𝗼𝘄𝗲𝗿 𝗼𝗱𝗲𝗿 𝗙𝗶𝗸𝘁𝗶𝗼𝗻? 𝗕𝗲𝗶𝗱𝗲𝘀 𝗴𝗲𝗵𝘁 𝗻𝗶𝗰𝗵𝘁.
Ich gehöre selbst zu denen, die gegen den Strom denken und unbequeme Themen anfassen. Gerade deshalb stört mich, was ich in diesen beiden Videos gesehen habe.
Denn wenn in dieser Szene Behauptungen ohne jeden Beleg als Enthüllung verkauft werden, trifft das am Ende alle, die ernsthaft hinterfragen. Wer über Reptiloiden lacht, lacht beim nächsten Mal auch über berechtig…
ICH HABE DEN STAAT ALS KIND KENNENGELERNT. SEINE METHODEN ERKENNE ICH BIS HEUTE.
Teil 9/9 – Der Wald ist weg. Meine Überzeugungen sind geblieben.
Ich bin 1968 geboren. Wir gehörten zu den Kindern, die den Haustürschlüssel um den Hals trugen, mit dem Fahrrad verschwanden und erst nach Stunden zurückkamen. Unsere Freiheit war kein pädagogisches Konzept. Sie war Alltag.
Wir kannten die Wege durch den Wald, die Gundwi…
ICH HABE DEN STAAT ALS KIND KENNENGELERNT. SEINE METHODEN ERKENNE ICH BIS HEUTE.
Teil 8/9 – Der Staat gehört nicht den Regierenden
Im Grundgesetz steht ein Satz, der eigentlich jede politische Diskussion über staatliche Macht begleiten müsste:
„Alle Staatsgewalt geht vom Volke aus.“
Artikel 20 Absatz 2.
Das bedeutet nicht, dass jede politische Entscheidung einer unmittelbaren Volksabstimmung bedarf. Unser Grundg…
ICH HABE DEN STAAT ALS KIND KENNENGELERNT. SEINE METHODEN ERKENNE ICH BIS HEUTE.
Teil 7/9 – Vertrauen lässt sich nicht verordnen
Ein Staat kann Gesetze erlassen, Verbote aussprechen, Bußgelder verhängen und seine Entscheidungen notfalls mit Zwang durchsetzen. Was er nicht kann, ist seinen Bürgern vorzuschreiben, ihm zu vertrauen.
Genau darin liegt ein Widerspruch, den ich seit meiner Jugend erkenne: Politische Mac…
ICH HABE DEN STAAT ALS KIND KENNENGELERNT. SEINE METHODEN ERKENNE ICH BIS HEUTE.
Teil 6/9 – Früher links, heute rechts? Ich habe meine Überzeugungen nicht gewechselt.
Ich bin inzwischen 58 Jahre alt. Ich habe Regierungen kommen und gehen sehen, erlebt, wie aus Rebellen Minister wurden, ehemalige Friedensaktivisten Aufrüstung befürworteten und sich politische Begriffe verschoben.
Was gestern links war, gilt heute p…
👏22❤17👍8
Showing the 12 most recent of 104 posts we hold for @taufertshoefer. 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.
Posts edited after publishing
@taufertshoefer edited 3 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
29 August 2026
Most recent edit
13 November 2026
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 9 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.
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.
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 12 November 2026 — this
entry's latest reading, not the date you are reading this.
“Rainer Taufertshöfer (öffentlich)” (@taufertshoefer), 13,809 subscribers as measured 12 November 2026. Telegram Register, tgregister.com/channel/taufertshoefer.
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.