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Channel

NEWHR — решаем задачи бизнеса с помощью найма

@newhr

On this record: Topic · Observations · Channels linked by matching posts · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry

9,279subscribers

-57 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001237441298
TypeChannel
Username@newhr
DescriptionNEWHR — международное рекрутинговое агентство 👉 Помогаем решать задачи бизнеса с помощью найма 👉 Делаем публичные и заказные исследования рынка 📩 [email protected] Наш канал про рекрутинг здорового человека: @docrecruiting
CreatedBetween 1 March 2018 and 31 July 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live11 November 2026
Measurements held27
Confirmed unchanged1 time, most recently 11 November 2026
On Telegramt.me/newhr

Topic

Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 11 September 2026 and assigned it the closest of 31 fixed categories, at 42% 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 1 other registered channel. This entry also forms a group of 2 channels linked by matching posts. 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)
Posted firstThenOverlapGap
@newhr/1144 · this entry24 Jul 2026, 09:28 UTC@docrecruiting/99124 Jul 2026, 09:29 UTC1.00under a minute
@newhr/1152 · this entry3 Aug 2026, 10:06 UTC@docrecruiting/9993 Aug 2026, 10:07 UTC1.00under a minute
@docrecruiting/100718 Aug 2026, 10:09 UTC@newhr/1159 · this entry18 Aug 2026, 10:09 UTC1.00under a minute
@newhr/1162 · this entry13 Oct 2026, 10:12 UTC@docrecruiting/101813 Oct 2026, 10:13 UTC1.00under a minute
@newhr/1163 · this entry16 Oct 2026, 13:19 UTC@docrecruiting/101916 Oct 2026, 13:19 UTC1.00under a minute
@newhr/1166 · this entry29 Oct 2026, 11:05 UTC@docrecruiting/102229 Oct 2026, 11:06 UTC1.00under a minute
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
ChannelMatching postsText overlapTypical gapPublished first
@docrecruiting9 (8/8 hand-verifiable sample passed)1.00under a minutethis entry (8–1)

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. 1 of the 1 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 23 July 2026 to 6 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 2 channels, the one whose matching posts we hold earliest is @newhr — 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 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 2 registered channels linked by matching posts. 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.

Growth

9,2769,3589,3176 August 2026 — 9,336 subscribers6 August 2026 — 9,336 subscribers6 August 2026 — 9,338 subscribers9 August 2026 — 9,347 subscribers12 August 2026 — 9,353 subscribers15 August 2026 — 9,352 subscribers18 August 2026 — 9,355 subscribers21 August 2026 — 9,349 subscribers25 August 2026 — 9,348 subscribers28 August 2026 — 9,354 subscribers31 August 2026 — 9,358 subscribers8 September 2026 — 9,348 subscribers12 September 2026 — 9,349 subscribers16 September 2026 — 9,346 subscribers25 September 2026 — 9,329 subscribers5 October 2026 — 9,323 subscribers11 October 2026 — 9,317 subscribers14 October 2026 — 9,320 subscribers17 October 2026 — 9,321 subscribers20 October 2026 — 9,312 subscribers23 October 2026 — 9,306 subscribers26 October 2026 — 9,301 subscribers29 October 2026 — 9,291 subscribers1 November 2026 — 9,284 subscribers4 November 2026 — 9,282 subscribers7 November 2026 — 9,276 subscribers11 November 2026 — 9,279 subscribers9,2796 August 202611 November 2026
27 measurements spanning 98 days, net -57. 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 9,264–9,370 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 27
Measured (UTC)SubscribersChange
11 Nov 2026, 17:219,279+3
7 Nov 2026, 14:099,276-6
4 Nov 2026, 13:179,282-2
1 Nov 2026, 17:369,284-7
29 Oct 2026, 09:389,291-10
26 Oct 2026, 13:569,301-5
23 Oct 2026, 08:369,306-6
20 Oct 2026, 14:069,312-9
17 Oct 2026, 08:169,321+1
14 Oct 2026, 15:379,320+3
11 Oct 2026, 00:589,317-6
5 Oct 2026, 02:009,323-6
25 Sept 2026, 22:599,329-17
16 Sept 2026, 21:429,346-3
12 Sept 2026, 17:379,349+1
8 Sept 2026, 17:179,348-10
31 Aug 2026, 11:359,358+4
28 Aug 2026, 13:439,354+6
25 Aug 2026, 03:039,348-1
21 Aug 2026, 21:189,349first reading

Engagement

15 posts held, back to 23 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 54 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
8.76%
avg views ÷ 9,279 subscribers
Avg views / post
813
7 posts measured
Reaction rate
1.21%
reactions ÷ views · ER floor
Posts in window
7
of 15 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
WindowRolling 30 days · latest post in window 13 November 2026
Posts held15 (23 July 2026 – 13 November 2026)
Views total5,693
Reactions total69
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken14 Nov 2026, 00:50 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
686
Videos
51
Links
512

Lifetime counters from Telegram’s own channel header, read 14 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Reaction mix

169 reactions across 15 posts, in 10 distinct kinds. The most used accounts for 33.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤5633.1%
🔥5029.6%
👍2716.0%
⚡127.10%
✍116.51%
❤‍🔥74.14%
😢21.18%
🦄21.18%
🤔10.592%
🤣10.592%

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 15 of the 15 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 169 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 15 most recent posts we hold, published 23 July 2026 to 13 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: 0 of 7 posts held from the last 30 days (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).

13 Nov 2026, 11:21 UTC320 views14 reactionsread 14 November 2026
Photo

💎 Кейс NEWHR: нашли Blockchain Engineer для децентрализованной AI-сети за месяц Нашему клиенту нужен был разработчик, который пишет сам блокчейн — тот код, на котором держится вся сеть. Специалист по сервисам и приложениям на готовом блокчейне не подходил. Новый инженер должен масштабировать протокол, выпускать обновления сети, искать уязвимости, работать над open-source-протоколом и взаимодействовать с open-source…

🔥6❤5👍3

6 Nov 2026, 11:39 UTC667 views8 reactionsread 14 November 2026
Photo

Чего бизнес сейчас хочет от HRD и Head of Recruiting, с учётом трансформации рынка и изменившихся задач бизнеса В октябре Кира Кузьменко, фаундер NEWHR, поговорила с 14 руководителями IT/Tech-компаний: 7 HRD и 7 Head of Recruiting. Спрашивала, чего от них хочет бизнес, как это меняет найм и саму HR-функцию и где в их работе уже есть AI. Если коротко: 👉 от HRD сейчас хотят экономии денег 👉 от Head of Recruiting — с…

❤4🔥2❤‍🔥1👍1

2 Nov 2026, 11:09 UTC798 views10 reactionsread 14 November 2026
Photo

🦔 Дайджест октября Рассказываем, что происходило в мультивселенной NEWHR в октябре. 🦹‍♂️ РАБОТОДАТЕЛЯМ 3 задачи, которые ставят себе HRD растущих компаний Full-stack HR, Product HR Manager и HR-инженер: новые роли для HR в 2026 году Какой рекрутер нужен бизнесу в 2026 году Исполнять задачу теперь может и ИИ. А за что платят человеку? Самые странные требования нанимающих менеджеров Принципы найма: на что Head …

❤5👍2🔥2❤‍🔥1

29 Oct 2026, 11:05 UTC848 views10 reactionsread 14 November 2026
Photo

На что Head of Analytics Эксмо смотрит в резюме аналитика? Это новый выпуск серии «Принципы найма», в которой нанимающие менеджеры рассказывают, как отбирают людей в свои команды! Герой выпуска — Лев Бирюков, Head of Analytics в Эксмо (крупнейшее книжное издательство России, 1500+ сотрудников). Сейчас активно переводит работу отдела на ИИ. Вот на что Лев обращает внимание в резюме 👇 ➖ Цифры Важно: само по себе н…

❤6👍2🔥2

22 Oct 2026, 11:39 UTC≈1,000 views12 reactionsread 14 November 2026
Photo

Три главных риска при найме проджектов по мнению нанимающего менеджера Запускаем серию материалов «Принципы найма», в которых нанимающие менеджеры рассказывают, как отбирают людей в свои команды! Если вы нанимающий менеджер или HR, эти инсайды — ваша возможность посмотреть на свой процесс со стороны. Мы подготовили этот материал, чтобы вы могли взять практические советы и идеи для вашего собственного найма. 🤓 Гер…

🔥6⚡3❤2👍1

19 Oct 2026, 15:15 UTC≈1,020 views9 reactionsread 14 November 2026
Photo

⭐️ Full-stack HR, Product HR Manager и HR-инженер: новые роли для HR в 2026 году Продолжаем рассказывать, как меняется профессия HR под влиянием кризиса и AI. Кира Кузьменко, фаундер NEWHR, проводит глубинные интервью с HRD и Head of Recruiting. По итогам этих разговоров она видит три тенденции, которые указывают на появление новых ролей в HR👇 🧑‍💻 Full-Stack HR Строго говоря, это возврат к истокам, когда один чел…

❤4🦄2😢2🔥1

16 Oct 2026, 13:19 UTC≈1,040 views6 reactionsread 14 November 2026
Photo

📣 HR-TECH: кто поведёт компанию в эпоху AI В июне 2026 года McKinsey опубликовало исследование HR Monitor 2026, основанное на опросе около 1 300 HR-специалистов и 5 500 сотрудников из десяти стран. Один из ключевых выводов: несмотря на потенциал AI, многие компании всё ещё находятся на стадии пилотных проектов. Масштабировать внедрение мешают разрозненные технологические решения и нехватка необходимых компетенций. …

👍2⚡1✍1❤1🔥1

13 Oct 2026, 10:12 UTC≈1,100 views6 reactionsread 14 November 2026
Photo

3 задачи, которые ставят себе HRD растущих компаний Кира Кузьменко, фаундер NEWHR проводит глубинные интервью с HRD и Head of Recruting о том, как меняются их роли и задачи. Полные данные исследования будут доступны только респондентам, но краткими результатами и инсайтами мы готовы поделиться уже сейчас. Вот три изменения в своей работе, которые HRD выделяют чаще всего 👇 1️⃣ Иначе оценивать кандидатов С учётом И…

❤3⚡1👍1🔥1

5 Oct 2026, 12:11 UTC≈1,270 views12 reactionsread 14 November 2026
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🤔 Исполнять задачу может теперь и ИИ. А за что платят человеку? Кира Кузьменко, фаундер NEWHR дала развёрнутый комментарий для РБК — про ИИ-навыки, зарплаты и найм. Ждём публикации статьи и делимся ответами Киры 🙌 💰 Влияют ли ИИ-навыки на зарплату? Да, конечно. Но что такое «ИИ-навыки» — это пока не устоявшееся понятие. Крупные компании, которые активно внедряют ИИ, уже дошли до отдельной сетки ИИ-компетенций для …

❤6👍3⚡1✍1🔥1

18 Sept 2026, 11:25 UTC≈1,520 views11 reactionsread 13 November 2026
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🔎 Ищем героев для 5 сезона подкаста «Собес»! Мы вовсю готовимся к запуску пятого сезона подкаста. Тема — трансформация найма и карьеры в эпоху AI. Через реальные истории людей Кира Кузьменко — IT-рекрутер и фаундер NEWHR — будет исследовать, как искусственный интеллект меняет найм прямо сейчас. Для тех, кто не знаком с подкастом 👇 «Собес» — подкаст про поиск работы, который мы делаем с 2022 года совместно с @libo…

❤4🔥3⚡2✍1❤‍🔥1

18 Aug 2026, 10:09 UTC≈1,950 views17 reactionsread 13 November 2026
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🎬 Прямой эфир — Найм 2026: адаптироваться нельзя паниковать 26 августа в 19:00 мск Кира Кузьменко идёт в гости к Sourcing School — на Sourcing Talks #13. На Sourcing Talks Егор Яценко и команда Sourcing School зовут гостей-практиков обсудить насущные проблемы сорсинга и рекрутмента. Открытые и честные разговоры, интерактивы, отсутствие цензуры. Трушно и по делу. Обсудим: ➖ А что вообще случилось? Сокращения, зам…

❤5🔥5✍4👍3

3 Aug 2026, 10:06 UTC≈1,870 views17 reactionsread 13 November 2026
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🍋‍🟩 Дайджест июля Собрали главное, что происходило в мультивселенной NEWHR, пока вы (возможно) были в отпуске. Если вы всё ещё там — кидайте фото в комментарии! Порадуемся за вас и слегка позавидуем. 🦹‍♂️ РАБОТОДАТЕЛЯМ Региональный EVP — ваш главный козырь или гарантия провала при международном найме «Хотим таких же, но дешевле». Что делать, если ваш бюджет не позволяет нанимать за те же деньги, что конкуренты? …

🔥6👍5⚡3❤2✍1

Showing the 12 most recent of 15 posts we hold for @newhr. 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.

Mentions

Named by 6 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.

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.

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.

Get IT
@Getitrussia · 22,054
Telegram ranks this channel #39 of 97 here — alongside 96 others — read 24 September 2026
DigitalHR (ДиджиталлЭйчАр): работа | вакансии | рекрутинг | стартапы
@digital_hr · 31,942
Telegram ranks this channel #43 of 100 here — alongside 99 others — read 6 September 2026
getmatch: канал про карьеру в IT
@g_jobchannel · 18,984
Telegram ranks this channel #46 of 95 here — alongside 94 others — read 5 October 2026
Job in IT&Digital
@geekjobs · 51,951
Telegram ranks this channel #69 of 98 here — alongside 97 others — read 25 August 2026
Job for Analysts & Data Scientists
@foranalysts · 37,897
Telegram ranks this channel #84 of 96 here — alongside 95 others — read 1 September 2026
RemoteGeekjob
@remotegeekjob · 26,005
Telegram ranks this channel #97 of 97 here — alongside 96 others — read 14 September 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 11 November 2026 — this entry's latest reading, not the date you are reading this.

“NEWHR — решаем задачи бизнеса с помощью найма” (@newhr), 9,279 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/newhr.

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.