Channel
@labor_one
On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
1,954subscribers
-3 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1001427773894 |
|---|---|
| Type | Channel |
| Username | @labor_one |
| Created | Between 1 April 2019 and 31 August 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 10 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 10 August 2026 |
| On Telegram | t.me/labor_one |
Politics & activism — 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 98% 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 |
|---|---|---|---|
| @english_learning_discuss/284416 May 2026, 11:59 UTC | @labor_one/12955 · this entry7 May 2026, 05:57 UTC | 1.00 | 18 hours |
| Channel | Matching posts | Text overlap | Typical gap | Published first |
|---|---|---|---|---|
| @english_learning_discuss | 5 (5/5 hand-verifiable sample passed) | 1.00 | 43 hours | @english_learning_discuss (5–0) |
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 1 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 7 comparable posts for this entry, running 7 May 2026 to 8 May 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 @english_learning_discuss. 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.
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 |
|---|---|---|
| 10 Aug 2026, 10:11 | 1,954 | -3 |
| 6 Aug 2026, 23:46 | 1,957 | no change |
| 6 Aug 2026, 23:36 | 1,957 | first reading |
10 posts held, back to 6 May 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 2 pagesof 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 10 posts for this entry, the most recent from 8 May 2026. An engagement rate over an empty window would be a number about nothing.
Measured directly from 1 video 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.
1 reaction across 1 post, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 1 | 100.0% |
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 1 of the 10 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 1reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 10 most recent posts we hold, published 6 May 2026 to 8 May 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.
你吃得越少，喝得越少，读得越少；你去剧院越少，去舞厅越少，去酒吧越少；你想得越少，爱得越少，思考得越少，唱歌越少，画画越少，运动越少；你存下的就越多，你坚不可摧的资产就越多。 然后你的存在变得越来越贫乏，你的生活变得越来越无趣，你的生命里真正表达出自身价值的部分越来越萎缩。你拥有的越多，你的生命就离你越远，你的内心就离你越远。 —— 卡尔·马克思，1844年 source
“你反对现有的专利政策？你是说那个发明iPhone的人，难道没有权利用自己的发明来挣钱吗？” 首先，我把这个评论贴出来举例子，不是为了嘲笑任何人。“发明某个东西的人用那个东西挣钱天经地义”的想法是一个很普遍的思维陷阱。这个思维陷阱基于的是作家安·兰德的思想 —— 某几个“伟大”的人创造了一切，并应得一切奖励。 iPhone很难说是“一种”发明，而是很多很多个发明的集合，包括液晶技术、晶体管技术、互联网、触摸屏、语音识别... 而所有这些技术的发明，都要感谢公共资金拨款支持，和无数拿着微薄薪资的研究人员的研究。 绝大多数受益广大人民的发明，都是很多很多人共同努力和共同支持下的产物。iPhone也不例外。某个伟大的天才白人在专利政策的激励下以一己之力创造出了某个东西，因此有权获得销售这个东西得来的巨资，只是资本主义创造出的神话而已。 source
telegra.ph/Index-of-klix4donline-05-08
=== 直面关于“家长权利运动”的四个谎言 === * 什么是“家长权利”运动？ 在加拿大各地，一些团体正以“家长权利”为名瞄准性少数学生，践踏性少数学生在学校的安全感和归属感，推动危及学生安全的政策，例如： 强制披露 - 强制学校在学生更改昵称或人称代词时告知家长。 限制使用 - 限制学生使用包容性洗手间和更衣室。 课程禁令 - 禁止或限制与性少数相关的教材或课程内容。 * 谎言一：“家长应该完全掌控孩子的生活” 孩子不是财产。 《加拿大权利与自由宪章》从没有提到“家长权利”几个字，它保障的是所有人的权利，包括儿童。 虽然《加拿大权利与自由宪章》赋予了每个人信仰和价值观的自由，但并不允许家长以此为由限制孩子的言论和表达自由。 1993年，加拿大法院裁定，在所有涉及孩子的情况下，必须优先考虑“孩子的最佳利益”。 在决定什么是“孩子的最佳利益”时，加拿大作为《联合国儿童权利公约》的签署国，承认： 儿童有权接受教育并形成自己的观…
❤1
这个世界上有两种人： 1. “我受过苦，所以你们也得受苦才公平。” 2. “我受过苦，所以我会竭尽所能让别人不再受我这份苦。” source
我觉得每个人都该思考这个问题 —— 当我看到什么样的人物形象的时候，我会觉得那一定是个心地残忍的人？ 在回答完这个问题之后，紧接着再问自己一个问题 —— 我这样的想法是哪里来的？ ❶ 如果在英雄片里，那个身体有残缺的形象一定是大魔头，那为什么经历过同样险峻的战斗的主角却从来不会因为战斗负伤而失去一条胳膊，或是一条腿，或是一只眼睛？ ❷ 为什么在科幻片里，反派的肤色都更黑？而主角的肤色都更白？ ❸ 为什么影片里贪婪成性的老板总是更胖？而主角总是更瘦？ ❹ 为什么谍战片里，反派的军师总是伤痕累累，而因为过去的战斗留下了深重心理阴影的主角却没有留下任何伤疤？ ❺ 为什么伺机害人的变态总是长着胡子化浓妆穿裙子的人？为什么从来没有跨性别女性成为主角？ ❻ 你打算维持这样的偏见吗？ ❼ 你打算让你自己创作的作品也充满这样的偏见吗？ 不要不加反思把你耳濡目染造成的偏见再次写进你的小说或同人文里。 另外，我看到评论里有很多人提到了影视文…
今天是五一劳动节，是全世界劳动者的节日。 我在想我们这些有身心障碍的人。我们中很多人因为工作而落下了残疾。我们中很多人完全不能工作了。我们中也有很多人正在工作，却不得不面临工作环境中的刁难。还有很多公司随意打压拖欠我们的薪资... 无论你处于什么情况，无论你遭遇过什么，我都为你还坚强地活着而高兴。你努力活在这个世界上，就是对我们这个世界的不公正的反抗。 source
在还未成年的时候，我曾经尝试过逃离家庭，却发现自己根本无法获得任何社会救济，只能在走投无路之后再次回到虐待我们的父母的身边。因此当看到有人故意曲解“儿童解放”这个概念的时候，我真的很生气。我们应该建设一个能允许曾经的我离开家庭获得庇护、为我自己和我弟弟的安全争取保障的社会，而这，就是“儿童解放”。 在这样一个社会里，遭到忽视的孩子们有权为自己争取必要的医疗服务。 在这样一个社会里，孩子们能接受到“如何为自己争取权利”的相关教育，学会如何为自己发声，有效表达自己的需求和意愿。 在这样一个社会里，所有人都必须以平等的态度对待孩子，尊重孩子的身体自主权，保障孩子不被剥削和虐待的权利；家长无权强迫孩子接受不必要的医疗干预（如强迫间性人孩子接受“性别矫正”），也无权禁止孩子接受医疗服务；同时，家长无权以“在家教学”为名隔离或监控孩子。所有从家长手中夺回的权利，必须回归孩子本人，而不是交由任何其它人代为行使。 “儿童解放”不仅仅是确保孩子…
我们本可以让每个人都有房子住。 我们本可以让每个人都有饭吃。 我们本可以照顾好每一个人。 我们本可以制造出质量更好的产品。 我们本可以根据人类和地球的需求来构建我们的生产体系。 从现有的资源来看， 这些都是可以做到的。 这也是为什么很多进步派会如此愤怒 —— 让所有人都能好好生活所需要的资源早已存在， 但我们现在却把这些资源送给富人去挥霍， 甚至把这些资源用来杀害穷人。 source
“我不能这么做，因为这么做有违我的信仰。” —— 这是信仰自由。 “你不能这么做，因为这么做有违我的信仰。” —— 这不是什么信仰自由。 source
Showing the 10 most recent of 10 posts we hold for @labor_one. 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.
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.
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 10 August 2026 — this entry's latest reading, not the date you are reading this.
“劳工之声” (@labor_one), 1,954 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/labor_one.
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.