Recycling and Reclamation Workers
Transportation and Material Moving Occupations- رمز O*NET-SOC
- 53-7062.04
Prepare and sort materials or products for recycling. Identify and remove hazardous substances. Dismantle components of products such as appliances.
تُعرض أسماء المهن وأوصاف المهام بالإنجليزية كما نُشرت. أما التسميات، ومنها أنواع المهام، فمترجمة.
التعرّض للذكاء الاصطناعي
- مصدر البيانات: BLSتاريخ النشر: 2026-08
منخفض· نسبي
منخفضأربع فئات نسبيةمرتفع جدًاقيمة على مستوى المجموعة المهنية
المقياس والأساس والمصدر
أربع فئات نسبية (منخفض / متوسط / مرتفع / مرتفع جدًا)
831 مهنة تفصيلية في جدول توقعات التوظيف لدى BLS. وتُسند القيمة على مستوى رمز مصفوفة التوظيف الوطنية (NEM)، فالمهن التي تشترك في الرمز نفسه تأخذ النطاق نفسه
- مصدر البيانات: Anthropicتاريخ النشر: 2026-03
0.000
0.000نطاق القيم المعروضة هنا0.745قيمة على مستوى المجموعة المهنية
المقياس والأساس والمصدر
مؤشر التعرّض المرصود، 0–1 كما نُشر
مربوط بمهام O*NET
منشورة لكل مهنة في SOC 2018؛ وكل مهنة في O*NET تحمل رمز SOC 2018 نفسه تأخذ هذه القيمة
- مصدر البيانات: ILOتاريخ النشر: 2025
0.09–0.14· 3 مجموعات ISCO-08
المقياس والأساس والمصدر
مؤشر التعرّض للذكاء الاصطناعي التوليدي، 0–1 كما نُشر
قيمة منشورة على مستوى مجموعة الوحدة في ISCO-08. رُبطت بهذه المهنة بتطبيق جداول التناظر الرسمية لمكتب إحصاءات العمل الأمريكي (BLS) (من ISCO-08 إلى SOC 2010، ومن SOC 2010 إلى SOC 2018) كما نُشرت، والتناظر كلي أو جزئي
ما نوع القيمة التي ينشرها هذا المصدر
فئة BLS رتبة نسبية لا مستوى مطلق، وليست قياسًا مباشرًا: فهي تجمع الرتب المئينية للمهنة في عدة دراسات منشورة في أربع فئات. وهي ليست توقّعًا للتوظيف أو الأجور، ولا احتمالًا للتبني، ولا تفرّق بين الأتمتة والتعزيز.
قيمة ILO لكل مجموعة ISCO-08 مرتبطة
- ISCO-08 9329Manufacturing Labourers Not Elsewhere Classified0.12
- ISCO-08 9333Freight Handlers0.14
- ISCO-08 9624Water and Firewood Collectors0.09
التعرض للذكاء الاصطناعي (معيار OpenAI)
18 مهمة مقيَّمة · 1 مهمة بقيمة β ≥ 0.5 (5.6%)
β = التعرّض المباشر (E1) + 0.5 × التعرّض عند توفر الأدوات (E2)، وفق تعريف المستودع المصدري.
- وحدة المصدر: مهام O*NET 27.2 ← رمز المهنة في O*NET 31.0
- عدد المهام المقيَّمة غير الموجودة في قائمة مهام O*NET 31.0: 4؛ وتبقى درجاتها كما نُشرت وفق O*NET 27.2.
- المصدر
- OpenAI "GPTs are GPTs" exposure rubric
- الإصدار
- gh-main-0471612
- الترخيص
- MIT License, Copyright (c) 2024 OpenAI
المهام
أوصاف المهام من O*NET® 31.0 Database، والمهام الأساسية أولًا.
| المهمة | النوع | β (OpenAI) |
|---|---|---|
| Sort materials, such as metals, glass, wood, paper or plastics, into appropriate containers for recycling. | أساسية | 0 |
| Operate forklifts, pallet jacks, power lifts, or front-end loaders to load bales, bundles, or other heavy items onto trucks for shipping to smelters or other recycled materials processing facilities. | أساسية | 0 |
| Sort metals to separate high-grade metals, such as copper, brass, and aluminum, for recycling. | أساسية | 0 |
| Clean recycling yard by sweeping, raking, picking up broken glass and loose paper debris, or moving barrels and bins. | أساسية | 0 |
| Clean, inspect, or lubricate recyclable collection equipment or perform routine maintenance or minor repairs on recycling equipment, such as star gears, finger sorters, destoners, belts, and grinders. | أساسية | 0 |
| Extract chemicals from discarded appliances, such as air conditioners or refrigerators, using specialized machinery, such as refrigerant recovery equipment. | تكميلية | 0 |
| Collect recyclable materials from curbside for delivery to designated facilities. | تكميلية | 0 |
| Deposit recoverable materials into chutes or place materials on conveyor belts. | تكميلية | 0 |
| Operate automated refuse or manual recycling collection vehicles. | تكميلية | 0 |
| Operate balers to compress recyclable materials into bundles or bales. | تكميلية | 0 |
| Operate processing equipment, such as fiber-sorters and grinders, to sort, crush, or grind recyclable materials. | تكميلية | 0 |
| Record logs of recycled materials or waste chemicals removed from products. | تكميلية | 1 |
| Clean materials, such as metals, according to recycling requirements. | تكميلية | 0 |
| Collect and sort recyclable construction materials, such as concrete, drywall, plastics, or wood, into containers. | تكميلية | 0 |
معلومات مهنية
المصادر والإسناد
This page includes information from the O*NET® 31.0 Database (https://www.onetcenter.org/database.html) by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O*NET® is a trademark of USDOL/ETA. AI Changing Work has modified all or some of this information: the O*NET-SOC code, title and task statements are reproduced in English without change; task-type labels are shown in the page's language and tasks are listed core first; any Korean occupation title shown on the Korean-language page is AI Changing Work's translation; any KSCO-8 unit groups linked to this occupation were paired with it by AI Changing Work's judgment, and the relation labels and statuses are AI Changing Work's additions. USDOL/ETA has not approved, endorsed, or tested these modifications.
Any AI exposure figures on this page are published by third parties, not by AI Changing Work, and none is part of the O*NET information. OpenAI publishes task-level scores (MIT License) for O*NET 27.2 task statements; each is shown next to the O*NET 31.0 task statement with the same task ID, whose wording can differ from the 27.2 statement that was scored. OpenAI also publishes occupation-level scores for O*NET-SOC codes in the same release, and any such score is shown on the O*NET occupation with the same code. Anthropic publishes an observed exposure index in the Anthropic Economic Index (CC-BY), and the U.S. Bureau of Labor Statistics publishes relative AI exposure categories (public domain); both are published per SOC code, and each value is shown on every O*NET occupation with that code. The International Labour Organization publishes a generative AI exposure index in ILO Working Paper 140 (CC BY 4.0) for ISCO-08 unit groups; AI Changing Work links those groups to O*NET occupations by applying the U.S. Bureau of Labor Statistics ISCO-08 to 2010 SOC and 2010 SOC to 2018 SOC crosswalks as published, without case-by-case selection, and these crosswalks match many groups only in part. Where several unit groups are linked, each group's published value is listed, and any summary shows only the lowest and highest of those values with the number of groups; no exposure figure is averaged or recalculated. Any employment figures are published by the U.S. Bureau of Labor Statistics for the SOC group containing this occupation. Each source is credited where its figures are shown.
O*NET OnLine: 53-7062.04 Recycling and Reclamation Workers
KSCO 코드·명칭: 한국표준직업분류(제8차 개정) — 통계청 고시 제2024-328호 (2024-07-01 고시, 2025-01-01 시행). 저작권법 제7조 제2호의 고시 항목이다. 명칭 표기(가운뎃점·띄어쓰기)는 해설서 2차 정오 반영판의 표기를 따랐으며, 고시 항목표와는 18개 명칭에서 가운뎃점 글리프나 띄어쓰기만 다르다. 통계청은 2025년 10월 국가데이터처로 개편되었다. 이 페이지의 KSCO 연결은 통계청·국가데이터처의 공식 연계표가 아니다.