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Exposed to Very Hot or Cold Temperatures

Work context · O*NET

Exposed to Very Hot or Cold Temperatures is a work-context dimension in the O*NET database — one of the standardized conditions O*NET uses to describe the environment a job is done in , grouped under Physical Work Conditions. O*NET defines it by asking workers: "How often does this job require working in very hot (above 90 F degrees) or very cold (below 32 F degrees) temperatures?." It is rated for 893 occupations, which average 2.28 out of 5 (moderate relative to other context dimensions).

How it's measured

O*NET rates each occupation on this dimension on a 1–5 context-importance scale (the CX scale), where higher means the condition is a more frequent or more central part of the work. The figures on this page are those occupation-level ratings — a description of working conditions as workers report them, not a judgment about pay, difficulty, or whether a job is "good."

Economy-wide average 2.28 / 5 Mean across all 893 rated occupations
Range across occupations 1.00–4.93 Lowest to highest occupation rating (spread 3.93)
Intensity vs. other dimensions 35th pct Where this dimension's average ranks among all O*NET work-context dimensions

Occupations where it's highest

The occupations that rate this condition strongest on the 1–5 scale.

Occupation Rating Score
Sailors and Marine Oilers 4.93
Driver/Sales Workers 4.82
Metal-Refining Furnace Operators and Tenders 4.82
Foundry Mold and Coremakers 4.74
Landscaping and Groundskeeping Workers 4.74
Refractory Materials Repairers, Except Brickmasons 4.74
Petroleum Pump System Operators, Refinery Operators, and Gaugers 4.69
Derrick Operators, Oil and Gas 4.68
Riggers 4.68
Meter Readers, Utilities 4.64
Wind Turbine Service Technicians 4.64
Service Unit Operators, Oil and Gas 4.61
Roustabouts, Oil and Gas 4.60
Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders 4.58
Structural Iron and Steel Workers 4.53
Gas Compressor and Gas Pumping Station Operators 4.51
Wellhead Pumpers 4.51
Construction Laborers 4.48
Biofuels Processing Technicians 4.45
Locomotive Engineers 4.45
Rotary Drill Operators, Oil and Gas 4.45
Mobile Heavy Equipment Mechanics, Except Engines 4.44
Industrial Truck and Tractor Operators 4.43
Brickmasons and Blockmasons 4.42
Crossing Guards and Flaggers 4.42

Occupations where it's lowest

The occupations that rate this condition weakest — where it is rarely part of the work.

Occupation Rating Score
Correspondence Clerks 1.00
Court Reporters and Simultaneous Captioners 1.00
Data Entry Keyers 1.00
Dermatologists 1.00
Family Medicine Physicians 1.00
Genetic Counselors 1.00
Hearing Aid Specialists 1.00
Lawyers 1.00
Medical Assistants 1.00
Medical Dosimetrists 1.00
Neuropsychologists 1.00
New Accounts Clerks 1.00
Ophthalmic Medical Technicians 1.00
Ophthalmic Medical Technologists 1.00
Optometrists 1.00
Oral and Maxillofacial Surgeons 1.00
Paralegals and Legal Assistants 1.00
Pediatricians, General 1.00
Pharmacists 1.00
Radiologists 1.00
Search Marketing Strategists 1.00
Skincare Specialists 1.00
Urologists 1.00
Video Game Designers 1.00
Watch and Clock Repairers 1.00

How AI is used by roles where exposed to very hot or cold temperatures is central

A working condition is not itself "being automated" — but we can look at the occupations where it is most central and ask how those people actually use AI. This rolls the Anthropic Economic Index per-role signal up across the roles that rate this condition 3 or higher (CX-rating-weighted). 39.0% of the 254 occupations where this condition is present carry observed AI-usage data (99 roles).

Across those roles, 29.4% of AI conversations are people working with AI and 31.2% hand a task to AI , with an average autonomy of 3.45 / 5.

Collaboration pattern Share What it means
directive 26.0% AI does it; you give the instruction
learning 18.6% you ask AI to explain or teach
task iteration 10.2% you and AI go back and forth
feedback loop 5.2% AI does it, then adjusts from your feedback
validation 0.6% you do it; AI checks your work

Roles behind this signal

The occupations where this condition is most central and that also have the most AEI data. "Works with AI" is the role's share of conversations that augment rather than automate.

Occupation Condition (1–5) Works with AI Autonomy
Cooks, Fast Food 3.1 45.8% 4.0/5
Soil and Plant Scientists 3.1 85.1% 4.0/5
Dietetic Technicians 3.1 48.8% 4.0/5
First-Line Supervisors of Landscaping, Lawn Service, and Groundskeeping Workers 4.2 18.5% 3.0/5
Cooks, Restaurant 3.0 36.7% 4.0/5
Food Scientists and Technologists 3.1 50.1% 3.5/5
Chefs and Head Cooks 4.4 38.5% 4.0/5
Industrial Machinery Mechanics 3.2 22.8% 4.0/5
Athletic Trainers 3.1 56.4% 4.0/5
Solar Photovoltaic Installers 4.1 47.2% 4.0/5
Inspectors, Testers, Sorters, Samplers, and Weighers 3.2 33.3% 3.0/5
Construction Managers 3.3 59.7% 3.0/5

Source: Anthropic Economic Index (2026-01-15-v4-plus-2025-03-27-v2) over a sample of Claude.ai Free and Pro conversations — not all AI tools and not the whole workforce. This is a role-weighted projection from AEI-linked occupations where this condition is central, not a direct measurement of AI use for the condition itself. Shares are weighted by how central the condition is to each role; some conversations are left unclassified by Anthropic's taxonomy, so shares need not sum to 100.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Exposed to Very Hot or Cold Temperatures." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27). Accessed June 7, 2026. https://singulariki.com/work-context/exposed-to-very-hot-or-cold-temperatures

APA

Singulariki. (2026). Exposed to Very Hot or Cold Temperatures. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/work-context/exposed-to-very-hot-or-cold-temperatures

BibTeX
@misc{singulariki-exposed-to-very-hot-or-cold-temperatures,
  title  = {Exposed to Very Hot or Cold Temperatures},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27). Accessed June 7, 2026},
  url    = {https://singulariki.com/work-context/exposed-to-very-hot-or-cold-temperatures}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.