Loading and Moving Machine Operators, Underground Mining

Construction and Extraction Occupations
O*NET-SOC 代码
47-5044.00

Operate underground loading or moving machine to load or move coal, ore, or rock using shuttle or mine car or conveyors. Equipment may include power shovels, hoisting engines equipped with cable-drawn scraper or scoop, or machines equipped with gathering arms and conveyor.

职业名称和任务陈述按其发布时的英文原文显示。标签(包括任务类型)为译文。

AI暴露度

  • 数据来源: BLS发布时间: 2026-08

    低· 相对

    低四级相对区间很高

    职业群单位数值

    尺度 · 母数 · 来源

    四级相对类别(低 / 中等 / 高 / 很高)

    以BLS就业预测表中831个细分职业为基数。取值按 NEM(全国就业矩阵)代码给定,因此共用同一 NEM 代码的职业得到相同分档

    来源数据集(XLSX 文件下载)

  • 数据来源: Anthropic发布时间: 2026-03

    0.000

    0.000此处所载数值的范围0.745
    尺度 · 母数 · 来源

    观测暴露度指数,按发布原值0–1

    以O*NET任务映射为基准

    按 SOC 2018 职业发布的数值;具有相同 SOC 2018 代码的所有 O*NET 职业均显示此值

    来源数据集(CSV 文件下载)

  • 数据来源: ILO发布时间: 2025

    0.17–0.20· ISCO-08 职业组 2 个

    尺度 · 母数 · 来源

    生成式AI暴露度指数,按发布原值0–1

    按 ISCO-08 细类(4 位)发布的数值。按原样应用美国劳工统计局(BLS)的官方对照表(ISCO-08→2010 SOC、2010 SOC→2018 SOC)关联到本职业,对应关系为全部或部分对应

    来源数据集(PDF 文件下载)

该来源发布的是什么性质的数值

BLS的类别是相对排位而非绝对水平,也不是一手测量:它把多项已发表研究给出的职业百分位排名归并为四个等级。它不是就业或工资预测,不是采用概率,也不区分自动化与增强。

各关联 ISCO-08 职业组的 ILO 数值
  • ISCO-08 8111Miners and Quarriers0.17
  • ISCO-08 8311Locomotive Engine Drivers0.20

AI 暴露度(OpenAI 评分标准)

已评分任务 28 项 · β ≥ 0.5 的任务 1 项(3.6%)

β = 直接暴露(E1)+ 0.5 × 借助工具时的暴露(E2),依据原始代码库的定义。

  • 原始单位:O*NET 27.2 任务 → O*NET 31.0 职业代码
  • 已评分任务中有 3 项不在 O*NET 31.0 任务列表中,其分数按 O*NET 27.2 的发布值保留。
来源
OpenAI "GPTs are GPTs" exposure rubric
版本
gh-main-0471612
许可
MIT License, Copyright (c) 2024 OpenAI

任务

来自 O*NET® 31.0 Database 的任务陈述,核心任务在前。

任务类型β(OpenAI)
Pry off loose material from roofs and move it into the paths of machines, using crowbars.核心0
Move trailing electrical cables clear of obstructions, using rubber safety gloves.核心0
Drive machines into piles of material blasted from working faces.核心0
Operate levers to move conveyor booms or shovels so that mine contents such as coal, rock, and ore can be placed into cars or onto conveyors.核心0
Clean hoppers, and clean spillage from tracks, walks, driveways, and conveyor decking.核心0
Oil, lubricate, and adjust conveyors, crushers, and other equipment, using hand tools and lubricating equipment.核心0
Replace hydraulic hoses, headlight bulbs, and gathering-arm teeth.核心0
Clean, fuel, service, and perform safety checks on all equipment, and repair and replace parts as necessary.核心0
Control conveyors that run the entire length of shuttle cars to distribute loads as loading progresses.核心0
Drive loaded shuttle cars to ramps and move controls to discharge loads into mine cars or onto conveyors.核心0
Examine roadway and clear obstructions from the path of travel.核心0
Handle high voltage sources and hang electrical cables.核心0
Measure, weigh, or verify levels of rock, gravel, or other excavated material to prevent equipment overloads.核心0
Monitor loading processes to ensure that materials are loaded according to specifications.核心0
Observe hand signals, grade stakes, or other markings when operating machines.核心0
Stop gathering arms when cars are full.补充0
Advance machines to gather material and convey it into cars.补充0
Signal workers to move loaded cars.补充0
Observe and record car numbers, carriers, customers, tonnages, and grades and conditions of material.补充0
Direct other workers to move stakes, place blocks, position anchors or cables, or move materials.补充0
Guide and stop cars by switching, applying brakes, or placing scotches, or wooden wedges, between wheels and rails.补充0
Maintain records of materials moved.补充1
Move mine cars into position for loading and unloading, using pinchbars inserted under car wheels to position cars under loading spouts.补充0
Push or ride cars down slopes, or hook cars to cables and control cable drum brakes, to ease cars down inclines.补充0
Read written instructions or confer with supervisors about schedules and materials to be moved.补充0

职业信息

来源与署名

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: 47-5044.00 Loading and Moving Machine Operators, Underground Mining

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.

完整署名与许可