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Channel

Эмма Каирова | Гура перевода

@translationguru

On this record: Growth · Engagement · Posts · Citations · Cite this entry

1,169subscribers

+1 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1001822038162
TypeChannel
Username@translationguru
Created11 April 2023measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/translationguru

Growth

1,1661,1691,167.56 August 2026 — 1,168 subscribers6 August 2026 — 1,168 subscribers9 August 2026 — 1,166 subscribers12 August 2026 — 1,169 subscribers6 August 202612 August 2026
4 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 1,166–1,169 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 16:341,169+3
9 Aug 2026, 14:141,166-2
6 Aug 2026, 08:511,168no change
6 Aug 2026, 03:221,168first reading

Engagement

15 posts held, back to 12 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 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
65.9%
avg views ÷ 1,169 subscribers
Avg views / post
771
13 posts measured
Reaction rate
1.96%
reactions ÷ views · ER floor
Posts in window
13
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 1 August 2026
Posts held15 (12 July 20261 August 2026)
Views total10,018
Reactions total196
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken6 Aug 2026, 08:51 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.

Recent posts

1 Aug 2026, 21:42 UTC≈203 views14 reactionsread 6 August 2026

вот эту мысль не могла вербализовать даже для себя, хотя давно чую этот подвох в тех стратегиях строительства личного бренда, который предлагают всякие там интернетные гуры

30 Jul 2026, 13:37 UTC≈587 views19 reactionsread 6 August 2026
Photo

в отличие от многих литературно одаренных коллег, которые поступали на пер- и филфаки с осознанным желанием переводить байронов и шекспиров, я никогда не считала, что буду иметь хоть какое-то отношение к переводу стихов или он ко мне а потом началась реальная работа и выяснилось, что копирайтеры любят рифмы в слоганах и теглайнах, а бренды — песни в видео-роликах (мазафака) что 99,9% авторов нехудожественных книг

25 Jul 2026, 18:34 UTC≈2,680 views20 reactionsread 6 August 2026

Осталось чуть больше двух месяцев до главного для переводчиков дня в году — Международного дня перевода. Последние пять лет мы праздновали его широкими онлайн-гуляниями в формате онлайн-конференции PROtranslation. В этом — приглашаем вас на переводческий образовательный форум Ассоциации преподавателей перевода, где PROtranslation выступит Grand-партнером и соорганизатором. Отдельной конференции в этом году не будет.

24 Jul 2026, 09:17 UTC≈390 views30 reactionsread 6 August 2026
Photo

у нейросети нет души, говорите?.. нейросеть, не умеет в юмор, думаете?.. мне тут дорогие коллеги нагенерировали пачку поздравительных текстов разных жанров, так я обревелась и обсмеялась

20 Jul 2026, 10:07 UTC≈366 views22 reactionsread 6 August 2026

и это, в принципе, отлично объясняет все наблюдения, которые я не понимала, чем объяснить: у нас на курсах — самые крутые и быстрые результаты показывают люди, которые не имеют вообще никакого языкового / лингвистического образования — особенно преуспевают всякие экономисты и менеджмент — 90% конфликтов и претензий к тому, что мы учим не тому и не так — от преподавателей и учителей; опечатки на слайдах — всегда гла

20 Jul 2026, 09:41 UTC≈317 views25 reactionsread 6 August 2026
Photo

озарилась озарением, пока читала #тп в последние несколько лет только и разговоров о том, что некий «чистый / обычный / просто перевод» как профессия уходит / ушел в прошлое из-за машпера и нейронок я все никак не могла понять концепцию этого «чистого / обычного / просто перевода», который отправила в историю просто очередная смена инструментов, которая в этой истории как будто не первая а пару дней назад как поня

17 Jul 2026, 16:37 UTC≈3,080 views17 reactionsread 6 August 2026
Photo

Приходите завтра слушать про анализ — где вам еще покажут такие веселые картинки заодно расскажу, почему ии не сможет заменить белковых переводчиков — и это вообще никак не связано с его якобы неумением в контекст, игру слов, иронию или что угодно еще, связанное в текстом: это он прекрасно как раз умеет в умелых руках — получше многих с естественным интеллектом

Showing the 12 most recent of 15 posts we hold for @translationguru. 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 — 14,524 of 1,176,251entries 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 2 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.

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 12 August 2026 — this entry's latest reading, not the date you are reading this.

“Эмма Каирова | Гура перевода” (@translationguru), 1,169 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/translationguru.

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.