Education — 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 89% 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 in near-verbatim form on 8 other registered channels. This entry also sits inside a group of 8 channels linked by matching posts, directly or through other channels in the group; two members of the group may share no posts 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 (6 of the pairs behind the counts below)
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
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. 23 of the 33 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 53 comparable posts for this entry, running 17 June 2026 to 9 November 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).
Of the group of 8 channels, the one whose matching posts we hold earliest is @start_v_IT. That is a statement about our reading window, not a claim of authorship.
Recorded under the keys clone_copy · clone_mutual · clone_source, last confirmed 11 November 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.
Channels linked by matching posts
This channel is in a group of 8 registered channels linked by matching posts, directly or through other channels in the group. This channel may share no posts with some of the channels listed below, and listed channels may share none with each other. Links are found by comparing text fingerprints across every channel on the register.
Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim 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.
27 measurements spanning 97 days, net -48. 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 8,654–8,749 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 27
Measured (UTC)
Subscribers
Change
11 Nov 2026, 00:20
8,665
-15
7 Nov 2026, 08:11
8,680
+6
4 Nov 2026, 06:34
8,674
-6
1 Nov 2026, 10:30
8,680
-4
29 Oct 2026, 17:09
8,684
-12
26 Oct 2026, 18:59
8,696
-1
23 Oct 2026, 20:55
8,697
-3
20 Oct 2026, 23:16
8,700
+5
17 Oct 2026, 18:08
8,695
+29
14 Oct 2026, 22:08
8,666
-3
11 Oct 2026, 21:58
8,669
-4
5 Oct 2026, 01:58
8,673
-20
26 Sept 2026, 06:38
8,693
-21
17 Sept 2026, 09:39
8,714
-3
13 Sept 2026, 10:38
8,717
-12
9 Sept 2026, 06:55
8,729
-4
4 Sept 2026, 08:16
8,733
-1
31 Aug 2026, 21:14
8,734
-4
28 Aug 2026, 22:34
8,738
+5
26 Aug 2026, 06:09
8,733
first reading
Engagement
53 posts held, back to 17 June 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 44 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
8.44%
avg views ÷ 8,665 subscribers
Avg views / post
731
10 posts measured
Reaction rate
0.205%
reactions ÷ views · ER floor
Posts in window
10
of 53 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 9 November 2026
Posts held
53 (17 June 2026 – 9 November 2026)
Views total
7,310
Reactions total
15
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
11 Nov 2026, 00:15 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.
Reaction mix
96 reactions across 50 posts, in 11 distinct kinds. The most used accounts for 31.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
30
31.3%
👍
20
20.8%
👏
13
13.5%
🔥
9
9.38%
🆒
6
6.25%
✍
5
5.21%
👀
5
5.21%
👌
5
5.21%
🐳
1
1.04%
😎
1
1.04%
🤗
1
1.04%
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 51 of the 53 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 96 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 53 most recent posts we hold, published 17 June 2026 to 9 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: 1 of 10 posts held from the last 30 days (10.0%) 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).
Освітній серіал "Стартуй стартап" на Дія.Освіта
Отже, ви вирішили створити стартап — що далі? Освітній серіал стане вашим гідом по основних етапах створення та пітчу стартапу.
Перевірте, чи готова ваша ідея, і чи ви можете називатися стартапом — канвас, портрет аудиторії, кастдев та валідація ваших гіпотез. Цьому можна навчитися у серіалі — він ще на крок наблизить вас до втілення інновацій.
Переглянути серіал мож…
Освітній серіал "Барбер" від Дія.Освіта
Блискуче лезо та точність рухів — барбершопи переросли у цілу культуру. Хочете стати барбером?
Як розвивалися барбершопи, які бувають види зачісок та як безпечно голити бритвою — дізнайтеся це, переглянувши освітній серіал. Навчіться робити зріз правильно — і тоді вас полюблять десятки клієнтів.
Переглянути цей серіал можете ТУТ
#безкоштовно
Найбільший у світі космічний хакатон знову в Україні!
ГО «Асоціація Ноосфера» вдесяте проводить NASA Space Apps Challenge й знову запрошує до участі всіх любителів космосу й технологій 🚀🪐
NASA Space Apps Challenge – це найбільший міжнародний космічний хакатон, який щороку проходить під егідою NASA у різних країнах. Десятки тисяч ентузіастів зі всього світу об'єднуються в команди і протягом 48 годин вирішують одне з…
Програма для команд, які хочуть навчитися залучати ресурси на власні проєкти
ГО «Моє місто» запускає «Краудстартер 3.0» — освітню програму для організацій, які прагнуть втілити свій проєкт у життя. Фокус на базових знаннях про фандрейзинг і краудфандинг
Що отримаєте:
🔸Персональний менторський супровід
🔸Онлайн-інтенсив: сталість на основі даних, архітектура стратегічного партнерства, міжсекторальні пропозиції та про…
🚀 Поки в класичному IT конкуренція зростає, український MilTech активно шукає нових фахівців.
За даними DOU, лише за перше півріччя 2026 року оборонні компанії опублікували 6523 вакансії — більше, ніж за весь 2025 рік.
І це не лише робота для військових чи інженерів.
Сучасний MilTech — це безпілотні системи, аналітика даних, розробка продуктів, тестування та технології, які безпосередньо впливають на обороноздатніс…
🟡 ЗНАЙДИ СВОЇХ: Кіновечір «Далласький клуб покупців»
Дивитимуться «Далласький клуб покупців» і говоритимуть про те, де закінчується турбота держави і починається твоє право вирішувати за себе. А ще про упередження, які ламаються, коли опиняєшся по один бік з тими, кого вчора зневажав.
👇Що буде:
🤝 нетворкінг-гра «Три кола»: знайомитесь швидко і без незручних пауз
🎬 перегляд фільму «Далласький клуб покупців»
💬 об…
Освітній серіал "Мистецтво готельного бізнесу" від Дія.Освіта
Цей серіал надасть базові знання про контроль якості готельних послуг на всіх рівнях комунікації гостя в готелі.
Експерти допоможуть посилити впевненість працівників готелю в доцільності сервісного обслуговування.
Зокрема, серіал містить робочі інструменти, що зроблять роботу працівників ефективнішою, а перебування гостя комфортнішим.
Переглянути цей с…
Для активних людей, які прагнуть бути в курсі всього важливого, представляємо добірку корисних каналів, поділену на розділи за тематиками. Розвивайтеся, вивчайте мови, знаходьте нову роботу та знайте все про бізнес і технології!
КАР'ЄРА ТА ВАКАНСІЇ
🥑 Workado — найбільший канал: пошук роботи та можливостей
🦖 Jobzilla UA — перевірені вакансії в ТОП компаніях
⚙️ Джун в IT — вакансії для розробників, QA, DevOps та інші…
🟡 ЗНАЙДИ СВОЇХ:
«Бідний Ван Гог, багатий Ван Гог»
За життя Ван Гог майже нічого не продав. Сьогодні його картини коштують мільйони. Що змінилося, якщо полотно лишилося тим самим? Розбираємось, хто насправді визначає цінність мистецтва.
Що буде:
🤝 Нетворкінг-гра «Три кола»: знайомство з новими людьми через питання, які справді хочеться обговорити
🎨 Лекція: історія Ван Гога як історія того, як народжується цінність…
✨ Безкоштовне навчання англійської мови з носіями для українських дітей 10–18 років!
Svitlo School запрошує українських дітей 10–18 років долучитися до безкоштовної онлайн-позашкільної освіти.
Розкажуть все на онлайн-вебінарі:
📅 25 жовтня 2026 року о 19:30 (за київським часом)
Що пропонує Svitlo School:
✅ уроки з носіями англійської мови
✅ академічні предмети англійською мовою
✅ гнучкий розклад — з 15:00 і до вечо…
А що, якби пошук роботи був простішим?
Готується програма про працевлаштування для молоді з інвалідністю — від складання резюме до проходження співбесіди.
Організатори прагнуть створити курс під реальні потреби учасників, а не здогадуватися про їхні запити.
Що найбільше заважає під час пошуку роботи? Чого саме не вистачає та які теми справді важливо розібрати?
📝 Кожен охочий може відповісти на кілька запитань і д…
💸 Безкоштовний курс фінансових навичок "Розраховую на себе" для жінок
Хочеш навчитися планувати бюджет, створювати фінансову подушку та ставити реальні фінансові цілі — а заодно розібратися з боргами, кредитами й першими кроками в інвестуванні?
Долучайся до безкоштовного курсу «Розраховую на себе» від Projector Foundation та Фундації Кредобанку. Вже понад 20 000 учасниць розібралися зі своїми грошима на попередніх …
❤2👍1
Showing the 12 most recent of 53 posts we hold for @bedeveloped. 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.
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 11 November 2026 — this
entry's latest reading, not the date you are reading this.
“Розвивайся! 💁 Майстер-класи, вебінари, курси різних напрямів” (@bedeveloped), 8,665 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/bedeveloped.
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.