Channel
@englishfoorpsychology
On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry
397subscribers
+0 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1001247857405 |
|---|---|
| Type | Channel |
| Username | @englishfoorpsychology |
| Description | سید محمد مهدی رئیس کرمی رتبه ۱ ارشد و ۵ دکتری https://t.me/englishfoorpsychology کانال آمار و روش 👇 @amaarravesh مشاوره @Miyanmind |
| Created | Between 1 March 2018 and 30 June 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 7 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/englishfoorpsychology |
Education — 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 100% 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.
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.
Posts published here appear word for word on 1 other registered channel. 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.
| Posted first | Then | Overlap | Gap |
|---|---|---|---|
| @englishfoorpsychology/590 · this entry14 Dec 2024, 09:09 UTC | @amaarravesh/23515 Dec 2024, 08:35 UTC | 1.00 | 23 hours |
| Channel | Matching posts | Text overlap | Typical gap | Published first |
|---|---|---|---|---|
| @amaarravesh | 10 (8/8 hand-verifiable sample passed) | 1.00 | under a minute | @amaarravesh (8–2) |
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 14 December 2024 to 4 June 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.
Across the whole group of 2, the earliest publisher we hold is @englishfoorpsychology — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_mutual, 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.
This channel’s posts match, word for word or near enough, posts on 1 other registered channel, 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 6 Aug 2026, 21:31 | 397 | no change |
| 6 Aug 2026, 21:20 | 397 | first reading |
19 posts held, back to 14 December 2024 — 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 4 June 2026. An engagement rate over an empty window would be a number about nothing.
Lifetime counters from Telegram’s own channel header, read 6 August 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.
8 reactions across 4 posts, in 2 distinct kinds. The most used accounts for 62.5% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 5 | 62.5% | |
| 👍 | 3 | 37.5% |
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 4 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 8reactions 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 14 December 2024 to 4 June 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.
با سلام و احترام وقت همگی به خیر با توجه به نزدیک شدن تایم دفاع ها، جهت فصل چهارم و محاسبات آماری و مشاوره مقاله و استخراج مقاله درخدمتم طبیعتا اولویت با عزیزانی هست که زودتر درخواست می دهند @Counselor96
♨️ آیا هوش مصنوعی مغز ما را تنبل میکند؟ ▪️پژوهش تازه MIT روی 54 دانشجو نشون میده استفاده زیاد از ChatGPT میتونه فعالیت مغز و حافظه رو کاهش بده. ▪️در این تحقیق سه گروه مقایسه شدن : 1. نوشتن مقاله با ChatGPT 2. نوشتن با کمک گوگل 3. نوشتن فقط با دانش خود ▪️نتیجه چیشد؟! مغز دانشجوهایی که از AI استفاده کردن، ارتباط کمتری بین بخشهاش نشون داد ؛ اونها سریعتر فراموش میکردن چی نوشتن و حس مالکیت کمتری روی متن داشتن. …
این کتب هم هست برای یکی از دوستان
کتاب های مدرسان فروخته شد سایر کتاب ها هم از منابع بسیار پرکاربرد ارشد و دکتری مشاوره هستند زبان ها هم بدرد همه رشته ها میخورن
Photo, posted without a caption
سلام دوستان وقت به خیر یک سری کتاب منبع اصلی و مهم کنکور ارشد و دکتری خودم هست. اگر کسی خواست پی وی در خدمتم. @Counselor96
سلام دوستان🌷 وقت به خیر یکی از دغدغه های اهالی روانشناسی، مشاوره و علوم تربیتی معرفی یک پیج اینستای علمی به والدین هست. پیج فرزندپروری میان یکی از همون هاست که واقعا میتونه کمک کننده باشه. با توجه به این که الان شروع پیجه داشتنش میتونه علاوه بر دیدن آموزش علمی، روند پیشروی یک پیج رو هم میتونه یاد بده خانه فرزندپروری میان https://www.instagram.com/miyanmind_?utm_source=qr&igsh=eXZqdGh1MnZyNm9h
English for psychology pinned Deleted message
با سلام و احترام با توجه به نزدیکی روزهای مصاحبه دکتری و ارائه پایاننامه و رساله ها لطفا عزیزان زودتر از موعدشون جهت انجام کارهای آماری و اصلاح مقاله و ... پیام بدن تا بنده هم بتونم برنامهریزی کنم. از پذیرش کارهای فوری معذورم چون طبق تجربه به کیفیت کار ضربه میزنه ... @AmaarAdmin
این مقاله بر نقش دو «محله» (Neighborhood) تأکید دارد: یکی در جهان بیرونی و دیگری در ذهن انسان. از منظر محیط بیرونی، Neighborhood Quality و Built Environment (نظیر دسترسی به فضاهای سبز، سطح امنیت، یا Service Conditions مانند مراکز عمومی و حملونقل) بر Mental Health و Psychological Well-Being افراد تأثیر میگذارند. عناصر Social Conditions مانند ارتباطات انسانی، اعتماد بین افراد و حمایت اجتماعی نیز نقش چشمگیری در پیشگی…
👍2
📊 هوش مصنوعی؛ کمک ساده و سریع در آمار و روش تحقیق! 🤖 سؤالی در مورد مفاهیم آماری یا روش تحقیق داری؟ کافیه بپرسی! توضیح میده، مثال میزنه و کمک میکنه راحتتر بفهمی. 🧮
English for psychology pinned «✨ یکی از شگفتیهای هوش مصنوعی که شاید ندونید: آموزش زبان انگلیسی! 🌟 📚 چی میشه باهاش انجام داد؟ تصور کنین ازش میخواین آزمون تعیین سطح طراحی کنه. 🎯 جوابا رو میدی و همون لحظه برات سطحت رو مشخص میکنه! بعدش؟ برنامهی آموزشی اختصاصی دقیقا برای هدفتون (مثل کنکور،…»
Showing the 12 most recent of 19 posts we hold for @englishfoorpsychology. 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 — 167,434 of 1,151,006entries 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
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.
Named by 1 registered channel — 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.
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.
@englishfoorpsychology named 1 handle 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.
References a handle that is not a live channel — we have no record it ever was one.
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 6 August 2026 — this entry's latest reading, not the date you are reading this.
“English for psychology” (@englishfoorpsychology), 397 subscribers as measured 6 August 2026. Telegram Register, tgregister.com/channel/englishfoorpsychology.
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.