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 10 August 2026 and assigned it the closest of 31 fixed categories, at 86% 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.
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. 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 (6 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 0 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 27 comparable posts for this entry, running 4 August 2026 to 7 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 2, the earliest publisher we hold is @DrTenpenny — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_source, last confirmed 8 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 1 other registered channel, 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.
61 measurements spanning 93 days, net -3,346. 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 87,099–91,449 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 61
Measured (UTC)
Subscribers
Change
7 Nov 2026, 12:01
87,601
-34
6 Nov 2026, 13:16
87,635
-35
5 Nov 2026, 15:56
87,670
-53
4 Nov 2026, 12:46
87,723
-18
3 Nov 2026, 10:15
87,741
-39
2 Nov 2026, 08:56
87,780
-1
1 Nov 2026, 08:55
87,781
-24
31 Oct 2026, 06:36
87,805
-34
30 Oct 2026, 07:21
87,839
-57
29 Oct 2026, 08:05
87,896
-18
28 Oct 2026, 04:07
87,914
-14
27 Oct 2026, 07:20
87,928
-19
26 Oct 2026, 07:15
87,947
-48
25 Oct 2026, 05:31
87,995
-15
24 Oct 2026, 07:45
88,010
-22
23 Oct 2026, 06:10
88,032
-51
22 Oct 2026, 06:08
88,083
-46
21 Oct 2026, 01:01
88,129
-20
19 Oct 2026, 23:15
88,149
-47
19 Oct 2026, 02:36
88,196
first reading
Engagement
813 posts held, back to 4 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 192 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
4.77%
avg views ÷ 87,601 subscribers
Avg views / post
4,180
252 posts measured
Reaction rate
2.37%
reactions ÷ views · ER floor
Posts in window
252
of 813 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 7 November 2026
Posts held
813 (4 August 2026 – 7 November 2026)
Views total
1,052,403
Reactions total
24,948
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Nov 2026, 19:20 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
≈17,300
Videos
≈3,430
Links
≈26,800
Lifetime counters from Telegram’s own channel header, read 7 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
4h 33m
Average length
1m 45s
Measured directly from 156 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
85,623 reactions across 803 posts, in 32 distinct kinds. The most used accounts for 19.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
16,886
19.7%
👍
16,808
19.6%
🤬
11,475
13.4%
🙏
11,082
12.9%
🔥
7,622
8.90%
👏
5,452
6.37%
🤮
5,069
5.92%
🤯
1,669
1.95%
😢
1,366
1.60%
👎
1,141
1.33%
🤣
1,041
1.22%
😁
994
1.16%
🤔
949
1.11%
😱
754
0.881%
🥴
737
0.861%
⚡
553
0.646%
😭
506
0.591%
🤨
383
0.447%
💔
366
0.427%
👀
219
0.256%
12 further kinds
551
0.644%
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 812 of the 813 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 86,736 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 813 most recent posts we hold, published 4 August 2026 to 7 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.
Telegram Stars
Stars received
5
across the posts below
Posts paid on
5
of 812 we hold a reading for · 0.6%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @DrTenpenny. 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 813 most recent posts we hold for this entry, published 4 August 2026 to 7 November 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.
Recent posts
Telegram’s own ‘edited’ marker: 23 of 252 posts held from the last 30 days (9.13%) 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).
“Deaths in the mRNA Flu Trial”: Calley Means Says Heidi Overton Pushed Moderna’s Flawed mRNA Flu Vaccine Through After Marty Makary Was Fired for sending it back for retrial
Calley Means described the handling of Moderna’s mRNA flu vaccine as another example of industry pressure overriding health concerns inside the Susie Wiles orbit.
Means said Moderna submitted the vaccine for FDA review. He claimed the agency id…
Our pre-Black Friday sale is happening now through November 11.
Stock up and save 20% with promo code EARLY.
Visit ShopEarly.DrTenpenny.com to browse the select supplements on sale.
Florida data shows much more harm from Pfizer than Moderna, but Moderna is certainly not off the hook.
Dr. Ladapo, Florida Surgeon General, speaks the truth.
The Tenpenny Report keeps a close eye on Pfizer and Moderna.
Here are our latest articles:
Florida Sues Pfizer: https://drtenpenny.com/florida-sues-pfizer/
Moderna Is A Very Murky Company.
Part 1: https://drtenpenny.com/moderna-is-still-a-very-murky-company…
This week's Morning Coffee is up on Rumble!
Two ways to watch.
Substack - https://drtenpenny.substack.com/p/morning-coffee-november-4-2026-edition
Rumble - https://rumble.com/v7hurk6-morning-coffee-with-dr.t-live.htm
The WHO has just approved two new candidate vaccines to join Ebola trial
WHY do we need MORE Ebola vaccines?
Expert groups convened by the World Health Organization (WHO) have recommended adding two new Ebola vaccine candidates to the ongoing Tumaini clinical trial in the Democratic Republic of the Congo (DRC). The recommendation marks the first time vaccines specifically designed to protect against Bundibugyo viru…
November 5, 2026 - Critically Thinking with Dr. T & Dr. P - Episode 306 - is up on Rumble!
RUMBLE
https://rumble.com/v7hydoq-critically-thinking-with-dr.-t-and-dr.-p-episode-306-nov-5-2026.html
Please follow us, like the video and share the link/channel with everyone you know!
Enjoy! XOXO
#CriticallyThinking #Prep4Survival #DrTenpenny
Hey all, I don't want to be a panican but there has been a major banking disruption in Japan.
A massive system failure crippled banking services at 128 financial institutions, impacting approximately 3,430 branches! ATMs stopped working, cash withdrawals and deposits were disrupted, and online banking services went dark!
People couldn't get their money.
https://endtimeheadlines.org/2026/11/system-failure-halts-at…
The chaos isn't random.
Kenneth Abramowitz believes Americans are looking at the country through the wrong lens.
We debate education, immigration, public health, national security, religion, China, Iran, and cultural decline as though each issue exists on its own. In The Multi-Front War: Defending America from Political Islam, China, Russia, Pandemics, and Racial Strife, Abramowitz argues those battles are connecte…
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❤12👍4🤮1
Showing the 12 most recent of 813 posts we hold for @DrTenpenny. 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
@DrTenpenny edited 12 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
8 August 2026
Most recent edit
2 November 2026
Posts recorded as deleted after publishing
We recorded 3 posts on @DrTenpenny as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
10 August 2026
Most recent seen missing
2 October 2026
Median time before seen missing
21 hours
Seen missing in the last 30 days
0
Polls
The 2 polls we hold for this entry, as Telegram rendered them when we read the post. A poll’s figures keep moving after that, so each one is dated.
Would you allow the Optimus robot to care for your health?
Yes, I welcome it2%
Get that thing as far away from me as possible81%
Not sure. I'd like more information18%
Shares as published, totalling 101%. No per-option vote count is published by Telegram, so none is shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 813 most recent posts we hold, published 4 August 2026 to 7 November 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republished by 86 registered channels. The 48 listed are the ones that have forwarded the most posts; the rest are counted here but not each listed.
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.
Handles this channel named that no longer answer
Dead references
4
handles named in this channel’s posts, vacant today
Evidenced gone
1
we ourselves saw one of these resolve, at some point
Never seen alive
3
vacant every time we have ever looked
@DrTenpenny named 4 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.
@melissaredpill named in 3 posts, 10 October 2026 – 28 October 2026 · confirmed gone 9 October 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.
@ericldaugh named in 3 posts, 10 October 2026 – 28 October 2026
@emfsol named in 1 post, 31 October 2026 – 31 October 2026
@dennisquaid named in 1 post, 21 August 2026 – 21 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 17 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.
Covid Vaccine Injuries @covid_vaccine_injuries · 24,619 Telegram ranks this channel #1 of 73 here — alongside 72 others — read 14 September 2026
Dirt Road Discussions @DirtRoadDiscussion · 130,977 Telegram ranks this channel #1 of 61 here — alongside 60 others — read 13 August 2026
Lee Merritt MD: FreedomDoc1 @FreedomDoc1 · 24,343 Telegram ranks this channel #2 of 75 here — alongside 74 others — read 16 September 2026
Christiane Northrup M.D @drchristianenorthrup · 41,003 Telegram ranks this channel #2 of 79 here — alongside 78 others — read 29 August 2026
Dr Jane Ruby @DrJaneRuby · 57,071 Telegram ranks this channel #2 of 81 here — alongside 80 others — read 22 August 2026
Dr. Judy Mikovits @dr_judymikovitss · 25,256 Telegram ranks this channel #3 of 82 here — alongside 81 others — read 14 September 2026
The TRUTH About Cancer | Vaccines @TheTruthAboutCancer_Vaccines · 28,333 Telegram ranks this channel #3 of 74 here — alongside 73 others — read 8 September 2026
Dr. Mercola @DoctorMercola · 30,859 Telegram ranks this channel #3 of 77 here — alongside 76 others — read 5 September 2026
Dr. Bryan Ardis @BryanArdis · 36,497 Telegram ranks this channel #3 of 73 here — alongside 72 others — read 1 September 2026
Children’s Health Defense @childrenshd · 52,454 Telegram ranks this channel #4 of 91 here — alongside 90 others — read 24 August 2026
Health Ranger @RealHealthRanger · 62,485 Telegram ranks this channel #4 of 82 here — alongside 81 others — read 21 August 2026
David Avocado Wolfe @davidavocadowolfe · 101,516 Telegram ranks this channel #4 of 69 here — alongside 68 others — read 15 August 2026
Health Nut News/Erin Elizabeth @erinhealthnutnews · 20,621 Telegram ranks this channel #5 of 81 here — alongside 80 others — read 24 September 2026
World Doctors Alliance @worlddoctorsalliance · 74,844 Telegram ranks this channel #5 of 88 here — alongside 87 others — read 19 August 2026
Stew Peters ✝️🇺🇸 @stewpeters · 132,655 Telegram ranks this channel #5 of 73 here — alongside 72 others — read 13 August 2026
Barbara O'Neill @barbara_oneill · 26,620 Telegram ranks this channel #6 of 67 here — alongside 66 others — read 11 September 2026
Dr. Simone Gold @DrSimoneGold · 79,055 Telegram ranks this channel #6 of 89 here — alongside 88 others — read 18 August 2026
Dr Naomi Wolf @NaomiWolfDr · 24,691 Telegram ranks this channel #7 of 87 here — alongside 86 others — read 14 September 2026
Independent Medical Alliance @IMA_Health · 30,997 Telegram ranks this channel #7 of 89 here — alongside 88 others — read 5 September 2026
COVID VACCINE VICTIMS AND FAMILIES @covid19vaccinevictims · 37,698 Telegram ranks this channel #7 of 69 here — alongside 68 others — read 31 August 2026
Hidden In Plain Sight @hiddeninplainsight1 · 38,130 Telegram ranks this channel #7 of 53 here — alongside 52 others — read 31 August 2026
Dr. Edward Group, DC @drgroupofficial · 19,574 Telegram ranks this channel #9 of 73 here — alongside 72 others — read 30 September 2026
Dr John B. @DrJohnB · 21,101 Telegram ranks this channel #9 of 85 here — alongside 84 others — read 23 September 2026
Dr. Lynn Fynn’s Science Enlightenment Channel & Stuff @DrLynnFynn · 23,921 Telegram ranks this channel #9 of 84 here — alongside 83 others — read 16 September 2026
This channel appears in 75 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Cross-platform identity — Wikidata
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.
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 7 November 2026 — this
entry's latest reading, not the date you are reading this.
“Dr. Tenpenny” (@DrTenpenny), 87,601 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/DrTenpenny.
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.