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 58% 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 3 other registered channels. They sit inside a group of 7 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 (2 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 19 comparable posts for this entry, running 1 July 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 7, the earliest publisher we hold is @LadyD_Q17. That is a statement about our reading window, not a claim of authorship.
Recorded under the keys clone_copy · 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 6 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.
33 measurements spanning 44 days, net -664. 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 24,185–25,049 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 33
Measured (UTC)
Subscribers
Change
18 Sept 2026, 23:21
24,285
-38
16 Sept 2026, 13:40
24,323
-22
14 Sept 2026, 19:19
24,345
-22
13 Sept 2026, 03:15
24,367
-40
11 Sept 2026, 05:55
24,407
-50
8 Sept 2026, 10:41
24,457
-39
5 Sept 2026, 06:36
24,496
-28
3 Sept 2026, 14:16
24,524
-33
2 Sept 2026, 05:34
24,557
-11
1 Sept 2026, 03:17
24,568
-14
31 Aug 2026, 02:43
24,582
-5
30 Aug 2026, 00:12
24,587
-11
28 Aug 2026, 22:27
24,598
-16
27 Aug 2026, 19:03
24,614
-23
26 Aug 2026, 16:42
24,637
-14
25 Aug 2026, 13:33
24,651
-17
24 Aug 2026, 10:26
24,668
-30
22 Aug 2026, 21:24
24,698
-27
21 Aug 2026, 14:44
24,725
-3
20 Aug 2026, 14:15
24,728
first reading
Engagement
139 posts held, back to 1 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 58 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
3.17%
avg views ÷ 24,285 subscribers
Avg views / post
770
69 posts measured
Reaction rate
—
this channel exposes no reaction counts
Posts in window
69
of 139 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 3 September 2026
Posts held
139 (1 July 2026 – 3 September 2026)
Views total
53,163
Reactions total
—
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Sept 2026, 10:39 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
1h 15m
Average length
49s
Measured directly from 92 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.
Satelloon retrieved from the ocean. Satellites are fake. Satelloons are the actual technology.
Join us: 🜂
Join and share my channel immediately:https://t.me/johndurhamchannel
Toads and Frogs are at the top of Creation. This has always been subconsciously known. They contain a noble essence that is near to the Heart of our Creator.
Join us: 🜂
Join and share my channel immediately:https://t.me/johndurhamchannel
🔻Take 3 milliliters in a glass of Orange juice twice a month. REMEMBER WHEN the Media laughed and said ivermectin is JUST for horses and cows? THEY KNEW It was made for Folks since 1987
What they left out👇
1 - It blocks Spike Protein entry to cells and if the person was vaccinated they can treat themselves for damage already done through Ivermectin. It prevents the damage done by drugs created using mRNA technology…
‼️ Finally, 🌎 is now on Telegram!
We used to think we had seen everything...
Until you subscribe to this channel 😱
It's really interesting 👇
Join and share my channel immediately:https://t.me/johndurhamchannel
🇺🇸 99% SOLD OUT — FINAL CHANCE! 🇺🇸
The FREE Trump Liberty $1 Coin is almost completely GONE!
🔥 99% of availability has already been claimed.
Only a tiny number remain — and once they’re gone, they’re GONE.
This special Trump Liberty $1 Coin is made for proud Americans who believe in FREEDOM, LIBERTY & AMERICA FIRST. 🇺🇸
🦅 YOUR COIN IS STILL AVAILABLE — BUT NOT FOR LONG.
👇 CLAIM YOUR FREE TRUMP LIBERTY $1 COIN NOW…
If you’ve been following this movement for any length of time, you already know the pattern.
Important information appears in certain places first.
Then it spreads.
Then the original sources become harder to find.
These five channels are currently among the most focused places for:
•
•
•
•
•
They are not general news channels.
They are built around the specific things many of us have been waiting for.
If …
Breaking: The War in Ukraine is a big loser (for everyone).
“Mr. President, if you were given access to reality-based, honest intelligence, you would be able to decide for yourself whose advisers have gotten it right over these past five years. And, once apprised of the reality on ground (and in the air), you might choose to do what is in your power to end the disaster in Ukraine.”
Signed: Veteran Intelligence Prof…
The people who stay quiet and wait usually miss the important moments.
The ones who stay connected and informed are the ones who understand what’s happening when things start moving faster.
Right now, these channels are actively following the key pieces:
•
•
•
•
•
This is not about hype.
It’s about staying close to the information while it’s still accessible.
These channels will not stay open forever in the…
The CCP has infiltrated every single institution in America bar none.
Xi is traveling around the world like he’s the new defacto world leader. As I type this he’s in Egypt negotiating how they can dominate the Suez Canal Zone (and to think, the U.S. gives Egypt $2B in U.S. taxpayer funding annually).
We need to come to grips with who we’re dealing with and China isn’t a nation that compromises on its ideology. When…
Showing the 12 most recent of 139 posts we hold for @johndurhamchannel. 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.
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.
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 16 September 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.
Mel Gibson @mel_gibsonchannel · 59,687 Telegram ranks this channel #69 of 72 here — alongside 71 others — read 22 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.
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.
“John Durham” (@johndurhamchannel), 24,285 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/johndurhamchannel.
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.