Literature — 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 22 September 2026 and assigned it the closest of 31 fixed categories, at 92% 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 (5 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. None of the 0 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 15 comparable posts for this entry, running 23 July 2026 to 4 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).
Of the group of 2 channels, the one whose matching posts we hold earliest is @jamalbeig — 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.
13 measurements spanning 97 days, net +22. 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 377–409 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
12 Nov 2026, 00:21
405
+2
4 Nov 2026, 13:20
403
+2
27 Oct 2026, 12:54
401
+1
21 Oct 2026, 09:51
400
+2
7 Oct 2026, 19:57
398
-2
26 Sept 2026, 23:40
400
+5
13 Sept 2026, 05:22
395
+5
5 Sept 2026, 18:16
390
+5
29 Aug 2026, 14:43
385
+3
22 Aug 2026, 23:06
382
+1
15 Aug 2026, 14:04
381
-2
6 Aug 2026, 20:17
383
no change
6 Aug 2026, 14:33
383
first reading
Engagement
20 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 1 page of 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 20 posts for this entry, the most recent from 4 August 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
65 reactions across 17 posts, in 7 distinct kinds. The most used accounts for 36.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
24
36.9%
👏
18
27.7%
👍
7
10.8%
😍
6
9.23%
💔
5
7.69%
😭
3
4.62%
👌
2
3.08%
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 17 of the 20 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 65 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 23 July 2026 to 4 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.
آیا زبان بعنوان یک پروسه ی تکاملی ،می تواند خود را به روز کند؟
به قلم: جمال بیگ
از دیدگاه «نظریه بینارشته ای فراگفتاریک» زبان را نه یک ابزار، که موجود زنده، پویا و خودسازمان دهنده می داند، بدین ترتیب پاسخ به سوال تیتر این مقاله مثبت است؛ اما با یک قید مهم: «زبان قواعد را تغییر نمی دهد، بلکه قواعد را بازتولید می کند».
دستور زبان در این نگاه، اسکلت ثابت زبان نیست؛ بلکه حافظه ی موقت آن است. همان گونه که استخوان های یک…
از دیدگاه فراگفتاریک، می توان اصل زیر را مطرح کرد:
«قاعده، پایان زبان نیست؛ حافظه موقت زبان است».
هرگاه زبان احساس کند قاعده ای مانع بقا، سرعت، موسیقی، یا انتقال مؤثر معناست، به تدریج آن را بازنویسی
می کند......
بنابراین، قواعد دستور زبان، فرمان های ابدی نیستند، انها «ایستگاه های موقت تکامل زبان» هستند. این نگاه، دستور زبان را از یک نظام بسته، به یک سامانه زنده، «فرگشتی و خوداصلاح گر» تبدیل می کند.
مخصوصن در این دوره…
به روایت فراگفتاریک آیا کلماتی که در شعر مخاطب را غافلگیر می کنند تاثیر گذارترند؟
به قلم: جمال بیگ
چند روز پیش در جلسه ی ادبی حضور داشتم که دوست شاعری پرسید آیا می شود در باره ی غافلگیری در شعر صحبت کنید؟..که ماحصل جواب را در اینجا با یک پاسخ کوتاه در رابطه با پرسش موضوع مقاله عرض کنم: که «نه همیشه»!!!؛ اما اگر غافلگیری از دل «ضرورت زبانی و عاطفی» زاده شود، معمولن اثری عمیق تر از واژه های قابل پیش بینی بر ذهن مخاطب …
«ایستادن بر جنگ های نوستالژیک» به روایت فراگفتاریک
به قلم: جمال بیگ
«جنگ نوستالژیک» لحظه ای است که «حافظه» خود را به جای «واقعیت» می نشاند. در این وضعیت، انسان بجای اینکه برای آینده بجنگد؛ برای تصویری اسطوره ای از گذشته می جنگد؛ گذشته ای که در ذهن، پالایش یافته، آرمانی شده و از تناقض های واقعی خود خالی گشته است. به همین دلیل، «جنگ نوستالژیک» بیش از آنکه نبردی بر سر سرزمین باشد، نبردی بر سر روایت هاست.
فراگفتاریک ا…
درود و احترام استاد گرامی🙏🌹
نوشتهتان را با دقت خواندم و با اصل دغدغهای که درباره ی بیمهری به هنرمند در زمان حیات و ستایش او پس از مرگ مطرح کردهاید کاملن همدل هستم. بهخصوص این نکته که ارزشگذاری واقعی یک جامعه نسبت به هنرمند، باید در زمان زیستن او اتفاق بیفتد نه فقط در مراسم بدرقه و سوگ که این همیشه دغدغه ی بزرگ خودم هم بوده و هست.
با این حال هنگام خواندن متن یک نکته به ذهنم رسید. به نظرم پدیدهای که از آن با عنو…
مهربانو پرنیان محتشم گرامی و ارجمند
درود و سپاس...امروز داشتم جوابیه ای در خور پرسش شما آماده می کردم که با متن ارسالی جناب زیارتی مواجه شدم که پاسخ پرسش شما را بخوبی به همراه دارد .برای همین متن را کوتاه کردم که در پایین برای شما ارسال می کنم ابتدا از اینکه متن «مرده خوری» را با دقت خواندید و با نگاهی نقادانه و در عین حال منصفانه، پرسشی اساسی را مطرح کردید.تشکر می کنم... به باور من، ارزش یک نظریه در مصون بودن از نقد…
(قسمت اول)
درود بر جناب جمال بیگ
باید عرض کنم که این نوشتار تحت عنوان فرا گفتار در عین اختصار چنان شبکهای از مفاهیم انتقادی را فعال میکند که میتوان آن را هستهی مرکزی یک نظریهی فرهنگی دربارهی سیاست مرگ در عصر رسانه دانست.
این حقیر بر خود دیدم که بر این گفتار ونوشتار زیبای دوست بزرگوار، نه عنوان نقد بلکه چند خطی جهت تحلیل و تکمیل آن که بسط فلسفی لایههای پنهان این نوشتار است افدام کنم که در حقیقت تلاشی …
(قسمت پایانی)
سلام مجدد
وقتی چند صدایی به یک صدایی تقلیل یافت
در آن لحظه، ما از نسبت (من-تو) به نسبت (من-آن) سقوط میکنیم و هنرمند را به مثابهی یک (موضوعِ سوگواری) مصرف میکنیم، نه یک (سوژهی گفتوگو)
نویسنده فراگفتار در تکمیلِ قسمت پایانیِ متن میگوید: (تنها صداست که میماند) : باید گفت این صدا، اگر راستین باشد، نه در آیینهای سوگواری پرشور، که در (گوشسپاری بیچشمداشت) به آنچه هنرمند در زمانِ حیات (بر زبان آور…
مرده خوری در سینما به روایت فراگفتاریک
به قلم: جمال بیگ
«مرده خوری» در سینما به غیر از بهره برداری از مرگ یک هنرمند، نوعی سازوکار زبانی و فرهنگی است که در آن، مرگ به سرمایه اساسی تبدیل می شود. در این وضعیت، انسان به حاشیه می رود و «روایت مرگ» جایگزین «زیست هنری» او می شود.
در خوانش فراگفتاریک، سینما یک نظام زنده از نشانه هاست. تا زمانی که هنرمند زنده است، زبان پیرامون او سرشار از نقد، رقابت، بی اعتنایی یا حتا حذف …
👏3❤2👍2
Showing the 12 most recent of 20 posts we hold for @jamalbeig. 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
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
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 12 November 2026 — this
entry's latest reading, not the date you are reading this.
“کانال ادبی فراگفتاریک ایران” (@jamalbeig), 405 subscribers as measured 12 November 2026. Telegram Register, tgregister.com/channel/jamalbeig.
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.