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Channel

Светлана Петровичева | про найм

@itrecruiting

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Telegram's recommendations · Cite this entry

11,865subscribers

-9 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001135246297
TypeChannel
Username@itrecruiting
CreatedBetween 1 June 2017 and 30 September 2020 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live31 August 2026
Measurements held22
Confirmed unchanged1 time, most recently 31 August 2026
On Telegramt.me/itrecruiting

Topic

Other / unclassifiable — 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 43% 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 1 other registered channel. They sit inside a group of 4 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 (5 of the pairs behind the counts below)
Posted firstThenOverlapGap
@techrecfamily/124028 Jul 2026, 14:01 UTC@itrecruiting/3635 · this entry29 Jul 2026, 09:08 UTC1.0019 hours
@techrecfamily/124329 Jul 2026, 15:27 UTC@itrecruiting/3637 · this entry30 Jul 2026, 13:04 UTC1.0022 hours
@techrecfamily/12484 Aug 2026, 11:28 UTC@itrecruiting/3640 · this entry4 Aug 2026, 11:43 UTC1.0016 minutes
@techrecfamily/12495 Aug 2026, 13:51 UTC@itrecruiting/3643 · this entry5 Aug 2026, 13:51 UTC1.00under a minute
@techrecfamily/12537 Aug 2026, 14:35 UTC@itrecruiting/3654 · this entry7 Aug 2026, 14:36 UTC1.00under a minute
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@techrecfamily6 (6/6 hand-verifiable sample passed)1.008 minutes@techrecfamily (60)

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 5 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 21 comparable posts for this entry, running 22 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 4, the earliest publisher we hold is @techrecfamily. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_copy, 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 3 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.

Growth

11,82711,87611,851.56 August 2026 — 11,874 subscribers6 August 2026 — 11,860 subscribers7 August 2026 — 11,854 subscribers8 August 2026 — 11,846 subscribers9 August 2026 — 11,841 subscribers10 August 2026 — 11,833 subscribers11 August 2026 — 11,857 subscribers13 August 2026 — 11,853 subscribers14 August 2026 — 11,849 subscribers16 August 2026 — 11,844 subscribers18 August 2026 — 11,837 subscribers19 August 2026 — 11,829 subscribers20 August 2026 — 11,827 subscribers21 August 2026 — 11,876 subscribers23 August 2026 — 11,872 subscribers24 August 2026 — 11,865 subscribers25 August 2026 — 11,856 subscribers26 August 2026 — 11,845 subscribers27 August 2026 — 11,847 subscribers28 August 2026 — 11,871 subscribers30 August 2026 — 11,868 subscribers31 August 2026 — 11,865 subscribers11,8656 August 202631 August 2026
22 measurements spanning 26 days, net -9. 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 11,820–11,883 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 22
Measured (UTC)SubscribersChange
31 Aug 2026, 21:3411,865-3
30 Aug 2026, 19:3711,868-3
28 Aug 2026, 18:4311,871+24
27 Aug 2026, 21:3711,847+2
26 Aug 2026, 21:5611,845-11
25 Aug 2026, 22:3711,856-9
24 Aug 2026, 20:4811,865-7
23 Aug 2026, 03:0911,872-4
21 Aug 2026, 12:2511,876+49
20 Aug 2026, 14:4211,827-2
19 Aug 2026, 16:3211,829-8
18 Aug 2026, 13:3411,837-7
16 Aug 2026, 06:1311,844-5
14 Aug 2026, 19:4411,849-4
13 Aug 2026, 12:0611,853-4
11 Aug 2026, 12:1611,857+24
10 Aug 2026, 15:0211,833-8
9 Aug 2026, 16:0111,841-5
8 Aug 2026, 18:5511,846-8
7 Aug 2026, 15:5011,854first reading

Engagement

55 posts held, back to 22 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 45 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
3.33%
avg views ÷ 11,865 subscribers
Avg views / post
395
42 posts measured
Reaction rate
0.714%
reactions ÷ views · ER floor
Posts in window
42
of 55 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. It is computed over the 26 of 42 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 31 August 2026
Posts held55 (22 July 202631 August 2026)
Views total16,599
Reactions total78
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken31 Aug 2026, 10:47 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
1m 25s
Average length
12s

Measured directly from 7 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

84 reactions across 29 posts, in 9 distinct kinds. The most used accounts for 39.3% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
3339.3%
👍1619.0%
🔥1315.5%
😁1113.1%
55.95%
🏆22.38%
👏22.38%
😍11.19%
🥰11.19%

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 35 of the 55 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 95 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 55 most recent posts we hold, published 22 July 2026 to 31 August 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

31 Aug 2026, 07:52 UTC296 viewsread 31 August 2026

ИИ повышает продуктивность сотрудников, но почти не влияет на прибыль компаний: по исследованию McKinsey, 76–81% работников и руководителей замечают рост личной эффективности, однако значительное увеличение EBIT — не менее чем на 5% — получили лишь 6% компаний. ИИ уже регулярно используют хотя бы в одном направлении 89% организаций, а 39% ждут связанного с ним сокращения штата в ближайший год — Коммерсантъ #ии #mcki

28 Aug 2026, 11:49 UTC127 viewsread 31 August 2026
Forwarded from @techrecfamilyVideo

AI для HR — это уже не “поиграться с ChatGPT”. Он может экономить часы на реальных задачах: — составить профиль вакансии; — подготовить интервью; — написать сообщение кандидату; — провести исследование рынка; — собрать аналитику; — помочь с сорсингом; — создать AI-ассистента под свою работу. Проблема одна: полезные промпты, инструкции и записи обычно разбросаны по десяткам чатов и сохранёнок. Поэтому мы сделали AI

28 Aug 2026, 07:52 UTC416 viewsread 31 August 2026
Photo

Наш мир всё стремительнее превращается в цикл взаимодействия ИИ друг с другом. Заметнее это всего становится в образовании. Пользуются искусственным интеллектом не только студенты, но и профессора. Вот преподаватель Калифорнийского университета в Беркли, на минуточку, этот универ входит в топы престижнейших вузов, признаётся, что использует ИИ для проверки студенческих эссе и составления рекомендаций. Времени у пре

27 Aug 2026, 15:04 UTC450 views0 reactionsread 30 August 2026
Photo

🤝 ТАКОЕ СКИДЫВАЮТ ТОЛЬКО ЛУЧШИМ ДРУЗЬЯМ Эту папку не выкладывают в общий доступ — её передают в личке со словами «только никому» 🤫 Считай, что тебе повезло. Внутри: 💼 свежие вакансии, удалёнка и фриланс каждый день 📈 как расти в карьере и зарплате быстрее коллег 🤖 AI-инструменты, о которых твой HR ещё не слышал 🗣 инсайды от рекрутеров и руководителей из первых рук 🧭 А чтобы не потеряться — внутри есть НАВИГАЦИЯ по

27 Aug 2026, 10:34 UTC450 views1 reactionsread 31 August 2026

✍️ Промпт дня: превратить внутреннюю заявку в вакансию, на которую хочется откликнуться Кандидату не нужен длинный список требований — ему важно быстро понять задачи, условия и смысл роли. Этот промпт поможет написать понятный текст вакансии без штампов, завышенных ожиданий и выдуманных преимуществ. Промпт для копирования: Ты — senior-рекрутер и редактор HR-текстов. На основе внутренней заявки подготовь понятное

🔥1

27 Aug 2026, 10:10 UTC137 viewsread 31 August 2026
Forwarded from @techrecfamilyVideo

Вы уже используете AI. Но используете ли вы его системно? У большинства HR и рекрутеров всё выглядит примерно так: — десятки сохранённых постов; — случайные промпты из Telegram; — несколько подписок на нейросети; — вебинары, которые некогда пересматривать. А когда появляется реальная задача, всё снова начинается с чистого листа. Поэтому мы создали AI HR Медиатеку — рабочую систему для ежедневных задач HR и рекрутин

27 Aug 2026, 07:43 UTC489 views1 reactionsread 31 August 2026
Photo

Готовы ли вы остаться в компании, если её акции резко обесценятся? Подобный вопрос задают в Anthropic на собеседованиях. Это гипотетический сценарий, через который проверяют потенциальных кандидатов. Похоже, что Дарио Амодею настолько не нравится, что люди с его фирмой только из-за денег, что вводят новые фильтры на стадии собеседования. Интересно, что даже для того, чтобы подготовиться к собеседованию в компанию,

1

26 Aug 2026, 15:03 UTC155 views3 reactionsread 31 August 2026
Forwarded from @techrecfamilyVideo

Если вы думаете, что AI HR Медиатека это просто большая библиотека материалов, то нет. Её ценность в другом: она помогает быстрее решать конкретные рабочие задачи. Например, с её помощью можно: — быстро собрать профиль вакансии; — подготовить структуру интервью и вопросы; — сделать исследование рынка и конкурентов; — ускорить сорсинг и поиск кандидатов; — написать письма кандидатам и отказные сообщения; — собрать с

3

25 Aug 2026, 09:28 UTC176 views1 reactionsread 31 August 2026
Forwarded from @techrecfamily

🧩 Промпт дня: провести встречу по снятию вакансии без бесконечных уточнений Размытая заявка приводит к нерелевантным кандидатам и спорам с нанимающим менеджером. Этот промпт поможет провести установочную встречу, отделить реальные требования от пожеланий и зафиксировать единые критерии подбора. Промпт для копирования: Ты — senior-рекрутер и консультант по подбору персонала. Подготовь сценарий встречи с нанимающим

1

25 Aug 2026, 08:01 UTC530 views1 reactionsread 30 August 2026

Неправильно спроектированное обучение стоит бизнесу денег И речь не только о стоимости разработки курса. Допустим, в программе оказалось всего 30 минут контента, который сотрудникам на самом деле не нужен. На обучение отправили 100 человек. Стоимость рабочего часа сотрудника составляет 1000 рублей. 100 сотрудников × 0,5 часа × 1000 ₽ = 50 000 ₽ Это стоимость только лишнего времени участников. А еще были часы метод

👍1

24 Aug 2026, 10:58 UTC184 views4 reactionsread 30 August 2026
Forwarded from @talent_huntersPhoto

Много вопросов: ✅ Как эффективно вести 6+ каналов самому? Где делегировать, где автоматизировать? ✅ Как не терять мотивацию вести телеграм канал при постоянных внешних изменениях? ✅ Какую стратегию выбрать: везде понемногу или глубоко и детально, но в 2-3 каналах/соцсетях? ✅ Как найти свой голос среди тысяч других, как выбирать партнёров, как расти? ✅ Если ты HR, карьерный консультант, коуч, психолог — как совме

2👍1🥰1

24 Aug 2026, 08:15 UTC592 viewsread 31 August 2026

Исследование LinkedIn показало, что из 38 профессий начального уровня 30 постепенно исчезают из-за ИИ: Бухгалтеры (-29%), графические дизайнеры (-28%), программисты (-27%), менеджеры по продуктам (-24%), аналитики данных (-15%), помощники юристов (-14%).

Showing the 12 most recent of 55 posts we hold for @itrecruiting. 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

@itrecruiting 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
19 August 2026
Most recent edit
19 August 2026

Citation-graph rank

Citation-graph rank — 292,127 of 1,629,419 entries 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

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.

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.

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.

Эйчаргейт| Перезагрузка
@hrgate · 55,780
Telegram ranks this channel #54 of 93 here — alongside 92 others — read 28 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 31 August 2026 — this entry's latest reading, not the date you are reading this.

“Светлана Петровичева | про найм” (@itrecruiting), 11,865 subscribers as measured 31 August 2026. Telegram Register, tgregister.com/channel/itrecruiting.

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.