Job listings — 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 76% 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 2 other registered channels. They sit inside a group of 6 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 (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 4 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 17 comparable posts for this entry, running 4 November 2025 to 6 July 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 6, the earliest publisher we hold is @romanci_knlu. That is a statement about our reading window, not a claim of authorship.
Recorded under the keys clone_mutual · clone_source, last confirmed 7 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 5 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.
3 measurements spanning 7 days, net +1. 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 398–399 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
14 Aug 2026, 00:27
399
+1
6 Aug 2026, 19:50
398
no change
6 Aug 2026, 17:50
398
first reading
Engagement
19 posts held, back to 9 October 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 19 posts for this entry, the most recent from 6 July 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
18 reactions across 6 posts, in 8 distinct kinds. The most used accounts for 33.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🤮
6
33.3%
❤
3
16.7%
😁
3
16.7%
👍
2
11.1%
💊
1
5.56%
💋
1
5.56%
🔥
1
5.56%
🥴
1
5.56%
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 8 of the 19 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 18reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 9 October 2025 to 6 July 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.
SPINNER Live - це провідний український постачальник продуктових рішень для іGaming компаній. 🎲
Маємо для тебе декілька вакансій:
🎤 Game Presenter
🃏 Shuffler
Пропонуємо:
✔️ графік роботи підлаштуємо під тебе
✔️ оплачуване навчання професії, яка матиме попит будь-де (досвід не потрібен)
✔️ ЗП вище середньої
✔️ зручний офіс у Києві
✔️ дружню команду та веселих колег-комфортіків
📩 Зацікавило? Пиши в Telegram: @Join…
Філологічний факультет освітніх технологій КНЛУ pinned «📱СТУДЕНТСЬКІ ТЕЛЕГРАМ КАНАЛИ КНЛУ: 📍ПІДСЛУХАНО В КНЛУ 📍KNLUCHAN 📍ДОШКА ОГОЛОШЕНЬ 📍KNLU CHAT 📍КНЛУ ГАЙДИ 📍ЦЕНТР КУЛЬТУРИ І МИСТЕЦТВ 📱TIK TOK KNLU 🤩ПО ФАКУЛЬТЕТАМ: 📣 ФАКУЛЬТЕТ ГЕРМАНСЬКОЇ ФІЛОЛОГІЇ І ПЕРЕКЛАДУ ✏️ ЧАТ ФГФіП 📣ФАКУЛЬТЕТ РОМАНСЬКОЇ ФІЛОЛОГІЇ…»
📱СТУДЕНТСЬКІ ТЕЛЕГРАМ КАНАЛИ КНЛУ:
📍ПІДСЛУХАНО В КНЛУ
📍KNLUCHAN
📍ДОШКА ОГОЛОШЕНЬ
📍KNLU CHAT
📍КНЛУ ГАЙДИ
📍ЦЕНТР КУЛЬТУРИ І МИСТЕЦТВ
📱TIK TOK KNLU
🤩ПО ФАКУЛЬТЕТАМ:
📣 ФАКУЛЬТЕТ ГЕРМАНСЬКОЇ ФІЛОЛОГІЇ І ПЕРЕКЛАДУ
✏️ ЧАТ ФГФіП
📣ФАКУЛЬТЕТ РОМАНСЬКОЇ ФІЛОЛОГІЇ І ПЕРЕКЛАДУ
✏️ ЧАТ ФРФіП
📣 ФІЛОЛОГІЧНИЙ ФАКУЛЬТЕТ ОСВІТНІХ ТЕХНОЛОГІЙ
✏️ ЧАТ ФОТ
📣 ФАКУЛЬТЕТ ТУРИЗМУ, БІЗНЕСУ І ПСИХОЛОГІЇ
✏️ ЧАТ ТУБіП
📣 ФАКУЛЬТЕТ СХІДНОЇ ТА С…
Вітаю!
У Києві понад 10 років діє чоловік, який систематично переслідує молодих дівчат, переважно студенток. Його улюблені локації: зупинки і вулиці біля НАУ, КПІ, КНТЕУ, КНУ, НУХТ, КНУТКіТ. Серед сотень потерпілих є неповнолітні.
Він застосовує відпрацьовану техніку тиску при першому контакті, після чого роками веде досьє на жертв, пам’ятає дати, маршрути, біографічні деталі, і повертається через 5-6 років.
Деталі…
Шукаємо менеджера по роботі з клієнтами
Хочеш розпочати кар’єру, але поки не маєш досвіду?
Ми готові навчити тебе та допомогти зробити перші кроки у стабільній та карʼєрній роботі.
Шукаємо активних студентів і спеціалістів-початківців на позицію менеджера по роботі з клієнтами.
Що потрібно робити:
- Спілкуватися з клієнтами та допомагати їм із питаннями
- Супроводжувати заявки та підтримувати якісний сервіс компані…
Філологічний факультет освітніх технологій КНЛУ pinned «📱ТЕЛЕГРАМ КАНАЛИ ВІД СТУДЕНТІВ - СТУДЕНТАМ: • ПІДСЛУХАНО В КНЛУ • KNLU CHAT • КНЛУ ГАЙДИ • ДОШКА ОГОЛОШЕНЬ КНЛУ • KNLUCHAN • ЦЕНТР КУЛЬТУРИ І МИСТЕЦТВ • 📱 TIK TOK KNLU 🤩ПО ФАКУЛЬТЕТАМ: 📣 ФАКУЛЬТЕТ ГЕРМАНСЬКОЇ ФІЛОЛОГІЇ І ПЕРЕКЛАДУ ✏️ ЧАТ ФГФіП 📣ФАКУЛЬТЕТ…»
📱ТЕЛЕГРАМ КАНАЛИ ВІД СТУДЕНТІВ - СТУДЕНТАМ:
• ПІДСЛУХАНО В КНЛУ
• KNLU CHAT
• КНЛУ ГАЙДИ
• ДОШКА ОГОЛОШЕНЬ КНЛУ
• KNLUCHAN
• ЦЕНТР КУЛЬТУРИ І МИСТЕЦТВ
• 📱 TIK TOK KNLU
🤩ПО ФАКУЛЬТЕТАМ:
📣 ФАКУЛЬТЕТ ГЕРМАНСЬКОЇ ФІЛОЛОГІЇ І ПЕРЕКЛАДУ
✏️ ЧАТ ФГФіП
📣ФАКУЛЬТЕТ РОМАНСЬКОЇ ФІЛОЛОГІЇ І ПЕРЕКЛАДУ
✏️ ЧАТ ФРФіП
📣 ФІЛОЛОГІЧНИЙ ФАКУЛЬТЕТ ОСВІТНІХ ТЕХНОЛОГІЙ
✏️ ЧАТ ФОТ
📣 ФАКУЛЬТЕТ ТУРИЗМУ, БІЗНЕСУ І ПСИХОЛОГІЇ
✏️ ЧАТ ТУБіП
📣…
📱ТЕЛЕГРАМ КАНАЛИ ВІД СТУДЕНТІВ - СТУДЕНТАМ:
• ПІДСЛУХАНО В КНЛУ
• KNLU CHAT
• КНЛУ ГАЙДИ
• ДОШКА ОГОЛОШЕНЬ КНЛУ
• KNLUCHAN
• ЦЕНТР КУЛЬТУРИ І МИСТЕЦТВ
• 📱 TIK TOK KNLU
🤩ПО ФАКУЛЬТЕТАМ:
📣 ФАКУЛЬТЕТ ГЕРМАНСЬКОЇ ФІЛОЛОГІЇ І ПЕРЕКЛАДУ
✏️ ЧАТ ФГФіП
📣ФАКУЛЬТЕТ РОМАНСЬКОЇ ФІЛОЛОГІЇ І ПЕРЕКЛАДУ
✏️ ЧАТ ФРФіП
📣 ФІЛОЛОГІЧНИЙ ФАКУЛЬТЕТ ОСВІТНІХ ТЕХНОЛОГІЙ
✏️ ЧАТ ФОТ
📣 ФАКУЛЬТЕТ ТУРИЗМУ, БІЗНЕСУ І ПСИХОЛОГІЇ
✏️ ЧАТ ТУБіП
📣…
👩🏼🏫 Репетитор англійської мови
✔️ 15 000 - 30 000 грн
📍 Віддалено
ANTISCHOOL - одна з найбільш популярних українських онлайн шкіл серед студентів.
Вимоги:
▪️Знати англійську на рівні В1 або вище;
▪️Можна без досвіду викладання або з мінімальним;
▪️Обожнювати викладати англійську та спілкуватись з людьми;
▪️Вміти зосередити увагу на собі та протримати її протягом усього уроку.
Умови:
▫️Гнучкий графік - години оби…
Привіт, друзі! Давно не бачились! Зима і нескінченні міти в Тімз остаточно випили всі соки? Досить сидіти з вимкненими мікрофонами – час виходити в офлайн!
Співаєш у душі? Танцюєш, розносиш стендапом чи вмієш щось таке, від чого в усіх відпаде щелепа?! Хочеш запалити сцену? Велкам, тобі до нас!
🌸 Що готуємо? Наймасштабніше весняне шоу талантів спільно з ЦКМ та студрадами.
🎯 Кого шукаємо? Талановитих студентів унів…
👩🏼🏫 Репетитор англійської мови
✔️ 15 000 - 30 000 грн
📍 Віддалено
ANTISCHOOL - одна з найбільш популярних українських онлайн шкіл серед студентів.
Вимоги:
▪️Знати англійську на рівні В1 або вище;
▪️Можна без досвіду викладання або з мінімальним;
▪️Обожнювати викладати англійську та спілкуватись з людьми;
▪️Вміти зосередити увагу на собі та протримати її протягом усього уроку.
Умови:
▫️Гнучкий графік - години оби…
Філологічний факультет освітніх технологій КНЛУ pinned «📱ТЕЛЕГРАМ КАНАЛИ ВІД СТУДЕНТІВ - СТУДЕНТАМ: • ПІДСЛУХАНО В КНЛУ • KNLU CHAT • КНЛУ ГАЙДИ • ДОШКА ОГОЛОШЕНЬ КНЛУ • KNLUCHAN • ЦЕНТР КУЛЬТУРИ І МИСТЕЦТВ • 📱 TIK TOK KNLU 🤩ПО ФАКУЛЬТЕТАМ: 📣 ФАКУЛЬТЕТ ГЕРМАНСЬКОЇ ФІЛОЛОГІЇ І ПЕРЕКЛАДУ ✏️ ЧАТ ФГФіП 📣ФАКУЛЬТЕТ…»
Showing the 12 most recent of 19 posts we hold for @pedagogy_knlu. 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.
Citation-graph rank
Citation-graph rank — 863,335 of 1,480,688entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
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 4 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
2
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
2
vacant every time we have ever looked
@pedagogy_knlu named 2 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.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@petoshina named in 1 post, 8 August 2026 – 8 August 2026
@work_languages_hr named in 1 post, 8 August 2026 – 8 August 2026
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 14 August 2026 — this
entry's latest reading, not the date you are reading this.
“Філологічний факультет освітніх технологій КНЛУ” (@pedagogy_knlu), 399 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/pedagogy_knlu.
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.