Local community — 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 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 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 2 other registered channels. 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. 10 of the 10 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 14 comparable posts for this entry, running 7 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 3, the earliest publisher we hold is @podolskadm. That is a statement about our reading window, not a claim of authorship.
Views per post sit far above this size band
112,000 average views per post against 91,686 subscribers — an engagement rate of 122.1%. Across the 8,270 registered channels in the same cohort — 31,627–99,994 subscribers, posting mainly in Russian — the middle half sit between 5.07% and 20.8%, with a median of 10.5%.
What this was computed from
Window
30 days (27 September 2026 – 27 October 2026)
Posts measured
173 of 173 published in the window (0 exact, 173 rounded by Telegram)
Views totalled
19,361,600
Mature posts only
126.1% over 77 posts read at least 24h after publication
When this is recorded. A channel is listed here only when its engagement rate sits at or above the 99th percentile of its cohort and is at least 3× away from that cohort’s median — above 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 keys clone_copy · clone_source · err_high, last confirmed 27 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.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 2 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.
51 measurements spanning 81 days, net -8,072. 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 85,953–101,559 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 51
Measured (UTC)
Subscribers
Change
27 Oct 2026, 03:48
91,686
-114
26 Oct 2026, 00:19
91,800
-118
25 Oct 2026, 01:19
91,918
-462
23 Oct 2026, 22:04
92,380
-134
22 Oct 2026, 21:37
92,514
-117
21 Oct 2026, 18:36
92,631
+4,877
20 Oct 2026, 12:20
87,754
-43
19 Oct 2026, 12:46
87,797
-149
18 Oct 2026, 10:04
87,946
-243
17 Oct 2026, 12:00
88,189
-1,362
16 Oct 2026, 09:37
89,551
-1,470
15 Oct 2026, 11:50
91,021
-1,876
14 Oct 2026, 14:59
92,897
-101
13 Oct 2026, 06:08
92,998
-421
9 Oct 2026, 00:37
93,419
-1,121
4 Oct 2026, 16:39
94,540
-1,032
26 Sept 2026, 14:01
95,572
-609
19 Sept 2026, 12:58
96,181
-129
17 Sept 2026, 00:57
96,310
-106
15 Sept 2026, 04:18
96,416
first reading
Engagement
440 posts held, back to 7 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 166 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
122.2%
avg views ÷ 91,686 subscribers
Avg views / post
112,000
175 posts measured
Reaction rate
0.219%
reactions ÷ views · ER floor
Posts in window
175
of 440 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 27 October 2026
Posts held
440 (7 August 2026 – 27 October 2026)
Views total
19,603,200
Reactions total
42,971
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
27 Oct 2026, 16:28 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
≈39,400
Videos
≈1,880
Links
≈2,930
Lifetime counters from Telegram’s own channel header, read 27 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
14m 22s
Average length
37s
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
82,070 reactions across 409 posts, in 7 distinct kinds. The most used accounts for 42.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
34,933
42.6%
👍
34,312
41.8%
❤
12,766
15.6%
👏
30
0.037%
💯
20
0.024%
👎
8
0.01%
🕊
1
0.001%
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 409 of the 440 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 82,070 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 440 most recent posts we hold, published 7 August 2026 to 27 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.
🤝 Подольские волонтёры собрали и передали бойцам СВО ценный груз
Маскировочные сети, спецоборудование, продукты, одежда, инструменты, канистры для топлива и масел — всё это совсем скоро окажется на Купянском направлении, в дорожно‑комендантском батальоне. Подразделение постоянно на ходу, так что любая помощь из тыла для ребят по-настоящему на вес золота.
Маскировочные сети плели буквально всем округом. К делу подкл…
«Сапфир» зажег огни восточного волшебства в Подольске 💎
В Доме культуры им. Лепсе отгремел фестиваль восточного танца «Сапфир» — уже третий по счёту, и в этот раз он побил все рекорды по масштабу. На сцену вышли свыше 200 танцовщиц из Москвы, Подмосковья и Владимирской области — от юных звёздочек до опытных мастериц. Среди коллективов — «Карима», «Сафира», «Данаб», «Жасмин», «Аль‑Сафир», «Тальяна», «Шамс», «Восточна…
🎉 Подольские закупщики — в числе лучших в стране
Управление закупочной деятельностью АО «НИИ НПО «ЛУЧ» второй год подряд доказывает свой высокий класс — по итогам исследования 2025 года команда вошла в топ‑100 всероссийского рейтинга премии «Лучшее управление закупочной деятельностью». В масштабном анализе участвовали свыше 500 руководителей закупочных подразделений крупных организаций, где годовой объём закупок пре…
Бронза с дебюта — крутой старт для юного подольчанина
Роман Алексеев, воспитанник подольского клуба «Скорпион», завоевал бронзовую медаль на всероссийских соревнованиях по универсальному бою в версии «Лайт». Турнир собрал более 170 спортсменов из 16 регионов России, а для команды «Скорпиона» эти состязания стали первым большим стартом. В возрастной группе 8–9 лет (вес до 45 кг) Роман, несмотря на отсутствие серьёзно…
☀️ Доброе утро, Подольск!
27 октября — Всемирный день аудиовизуального наследия: отличный повод вспомнить, как много хранят в себе старые фото, фильмы и записи.
А ещё сегодня православные чтут память преподобной Параскевы Сербской — с этого дня раньше начинали готовиться к холодам. Погода радует: +10 °C, ветер 3 м/с.
Киновечер с ностальгией: смотрим «Весну на Заречной улице» вместе 🎥
В Подольске для участников клуба «Активное долголетие» готовят особенный вечер: 27 октября в МЦ «Территория будущего» покажут легендарную советскую картину «Весна на Заречной улице».
Долголеты не просто посмотрят фильм на большом экране — их ждёт рассказ о том, как снимали ленту, интересные факты из жизни актёров и живое обсуждение после показа. Бу…
💪 Подольск помогает героям: 10 адаптированных рабочих мест для ветеранов СВО с инвалидностью
В Подольске продолжают поддерживать участников специальной военной операции и ветеранов боевых действий — и одно из самых важных дел здесь: помочь ребятам вернуться к мирной жизни и найти своё место в профессии. Чтобы работа была комфортной, в военном комиссариате городского округа оборудовали 10 специально адаптированных ра…
Подольский филиал Мособллеса — в топе по расчистке лесов 🌲
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На сцене прозвучат его произведения в исполнении солистов МАМТ и Подольской филармонии, Академического хора (дирижёр Кирилл Краюшкин) и Концертного оркестра (дирижёр Марат Акберов).
📆…
☀️ Доброе утро, Подольск!
26 октября православные отмечают праздник Иверской иконы Божией Матери — к этой святыне испокон веков обращались за поддержкой. А по народному календарю день называли Банным обиходом: предки наводили порядок в бане и собирались на тёплые посиделки.
Сегодня по-осеннему свежо: +9 °C, ветер 5 м/с — самое время укутаться потеплее.
🔥 Подольские наставники «Движения Первых» зарядились новыми идеями на региональном слёте!
Педагоги из Подольска стали частью большого образовательного события — они поучаствовали в региональном слёте наставников Московской области, который прошёл в спортивно‑оздоровительном комплексе Одинцовского филиала МГИМО.
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❤118👍110🔥90
Showing the 12 most recent of 440 posts we hold for @gorod4967. 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
@gorod4967 edited 1 post 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
25 September 2026
Most recent edit
25 September 2026
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
Named by 1 registered channel — 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.
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 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.
Подольск | События | Подслушано @Podolsk_podslushal · 36,394 Telegram ranks this channel #4 of 61 here — alongside 60 others — read 1 September 2026
Григорий Артамонов | Подольск @GrArtamonov · 26,057 Telegram ranks this channel #6 of 89 here — alongside 88 others — read 13 September 2026
ПОДОЛЬСК | СОБЫТИЯ | НОВОСТИ @Podolsk_nov · 22,544 Telegram ranks this channel #9 of 48 here — alongside 47 others — read 20 September 2026
Типичный Подольск @tipichniypodolsk · 28,392 Telegram ranks this channel #17 of 56 here — alongside 55 others — read 9 September 2026
Официальный Подольск @podolskadm · 29,868 Telegram ranks this channel #18 of 78 here — alongside 77 others — read 7 September 2026
Новости правда @newsprav_da · 181,622 Telegram ranks this channel #22 of 73 here — alongside 72 others — read 11 August 2026
This channel appears in 6 seed channels' Telegram-generated recommendation lists 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 27 October 2026 — this
entry's latest reading, not the date you are reading this.
“Подольск 24\7” (@gorod4967), 91,686 subscribers as measured 27 October 2026. Telegram Register, tgregister.com/channel/gorod4967.
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.