Median annual wage
$101,530CaliforniaSpecial education teachers, middle school job market in California
Industry trends, wages and hiring signals.
Data availability
Published industry context is limited
The report below shows the available evidence. Missing figures are not estimated.
Occupation pay
What Special education teachers, middle school earn in California
BLS OEWS occupation-level pay estimates for this role — separate from the industry wage trends used elsewhere in this report.
- Middle 50% of published wages
- $80,550 – $120,550
- U.S. median annual wage
- $66,810
- Reference period
- May 2025
The middle 50% is the 25th-to-75th percentile wage range, not an experience-level band. Suppressed or unavailable BLS values remain unpublished rather than being estimated.
Pay around California
How median pay varies by metro area
Published BLS OEWS metro estimates for Special education teachers, middle school, compared with the California median of $101,530.
California median$101,530
San Jose-Sunnyvale-Santa Clara, CA$121,070+19.2% vs. state
Sacramento-Roseville-Folsom, CA$110,850+9.2% vs. state
Fresno, CA$104,540+3.0% vs. state
San Francisco-Oakland-Fremont, CA$103,580+2.0% vs. state
Los Angeles-Long Beach-Anaheim, CA$101,560Same as state at displayed precision
Salinas, CA$100,840−0.7% vs. state
View 7 more published metro areas
Riverside-San Bernardino-Ontario, CA$99,190−2.3% vs. state
Santa Rosa-Petaluma, CA$97,000−4.5% vs. state
Modesto, CA$96,500−5.0% vs. state
Oxnard-Thousand Oaks-Ventura, CA$82,290−19.0% vs. state
San Diego-Chula Vista-Carlsbad, CA$79,310−21.9% vs. state
Stockton-Lodi, CA$78,290−22.9% vs. state
San Luis Obispo-Paso Robles, CA$73,630−27.5% vs. state
Areas are ordered by published median wage for readability, not as an overall job-market ranking. The vertical marker is the California median. Some BLS metropolitan areas cross state lines, so a metro estimate can cover workers in more than one state.
Local research
What the data shows for special education teachers, middle school in California
Findings describe the published observation periods shown below. Research published Oct 11, 2026.
The highest-paying metro has a smaller employment market
The OEWS May 2025 comparison for California shows a pay premium alongside a smaller employment estimate. San Jose-Sunnyvale-Santa Clara, CA's median annual pay of $121,070 is 19.2% higher than Los Angeles-Long Beach-Anaheim, CA's $101,560, while their employment estimates are 360 and 2,030, respectively. Among 10 metros with both usable measures, the former has the highest median pay and the latter the largest employment estimate. These counts describe existing jobs, not available vacancies.
OEWS May 2025 · BLS OEWSSome metro estimates cross state lines. Higher nominal pay does not establish better living standards or better chances of finding a job.
This occupation is less concentrated in the state
Employment concentration provides a different comparison for special education teachers, middle school in California. In OEWS May 2025, the published location quotient is 0.44, meaning the occupation's share of employment is 0.44 times its national share. The state estimate is 4,860 jobs, 5.1% of the national employment estimate for this occupation. It represents 0.27 jobs per thousand jobs in the state's OEWS employment universe. This measures existing employment concentration, not current hiring or future growth.
OEWS May 2025 · BLS OEWSOEWS employment estimates describe covered wage-and-salary jobs and exclude self-employed workers; location quotients do not measure vacancies or worker demand.
Published median pay is above the U.S. median
OEWS May 2025 records a state median annual wage of $101,530 for special education teachers, middle school in California. Against the national median of $66,810, that is 52.0% higher. A median describes the middle of the distribution and does not include a living-cost adjustment.
OEWS May 2025 · BLS OEWSFindings describe published data and do not establish causes. Methodology
Current market signals
Recent statewide layoff-notice context alongside the published BLS figures below. This signal does not feed the Job Market Health score.
Statewide WARN notices
California statewide313 notices in this source
Notice dates from Aug 5, 2026 to Nov 2, 2026 (UTC), a rolling 90-calendar-day period.
What this means: This is the number of WARN notices with notice dates in this period in California’s official statewide list. It is a statewide count only, and does not identify any employer.
Notices describe planned workforce changes, not confirmed job losses. Notices may be amended or withdrawn. This statewide context is not occupation-specific and does not affect the Job Market Health score. WARN covers qualifying large layoffs and closures under applicable law, not all layoffs, and thresholds vary by state.
California Employment Development Department About WARN data
Source last checked
Indeed job postings · California
Recent hiring-demand context · separate from the health score
86.5Postings index · February 1, 2020 = 100Observation: Oct 23, 2026
-13.5%Versus the February 2020 baseline
0.0%Change over about four weeksSep 25, 2026 to Oct 23, 2026
This is statewide demand across all occupations, not demand for this specific job. Postings are not a count of vacancies or hires, and Indeed does not cover the entire labor market.
Source: Indeed Hiring Lab · CC BY 4.0. Seven-day average, seasonally adjusted; publisher refreshes weekly and may revise history. Retrieved Nov 1, 2026 · saved source copy. JobMarketHealth calculates the displayed changes and samples weekly observations for the chart.
+4.4%Industry employmentU.S. +2.2%State data coverage: 100%
+12.9%EstablishmentsU.S. +7.1%State data coverage: 100%
+0.8%Avg. weekly industry wageU.S. +2.3%State data coverage: 100%
890,525Represented establishmentsEstablishments in the industries that employ this occupation, not employers hiring itIndustry mix share 100.0%, separate from the data coverage on the trend cards
Industry employment change over time
Year-over-year change for the industries that employ Special education teachers, middle school in California · percentage change
Year-over-year employment change (%) by reference quarter
Latest published values
- California · 2026 Q1+4.4%
The chart will load automatically. Published values remain available in this report.
Every published quarter
BLS does not publish a national quarterly series for this occupation’s industry mix, so only the California series is shown. The U.S. figure on the cards above is the latest quarter benchmark.
| Quarter | California | State data coverage |
|---|---|---|
| 2024 Q2 | +6.0% | 100% |
| 2024 Q3 | +6.1% | 100% |
| 2024 Q4 | +6.5% | 100% |
| 2025 Q1 | +4.7% | 100% |
| 2025 Q2 | +5.8% | 100% |
| 2025 Q3 | +5.4% | 100% |
| 2025 Q4 | +4.9% | 100% |
| 2026 Q1 | +4.4% | 100% |
Industry mix behind this view
Which industries are weighted into this view. Not a ranking of employers or of job quality.
| Industry group | Share of occupation employment | Local employment change | Establishments | Avg. weekly wage |
|---|---|---|---|---|
| Private education and health services | 99.9% | +4.4% | 890,525 | $1,277 |
The publication date above is the official BLS news release date for this reference quarter, linked to the notice. The values match the snapshot independently checked against BLS sources on September 17, 2026. The publication date identifies the quarterly news release, not the exact revision date. The data period above is the quarter the figures describe.
QCEW describes the industries that employ this occupation, not the occupation itself. It is not a count of job openings and is not part of the 0-100 Job Market Health score.
Evidence record
Derived by JobMarketHealth from BLS QCEW + published occupation industry mix. This is occupation-weighted industry context, not direct occupation employment and not a count of current job openings.
- Occupation
- Special education teachers, middle school
- SOC code
- 25-2057
- State
- California
- QCEW release label
- QCEW 2026 Q1
- Data period
- 2026 Q1
- State industry employment, year over year
- +4.4%State data coverage 100%
- U.S. benchmark, year over year
- +2.2%
- Difference from U.S. benchmark
- +2.2 percentage pointsPercentage-point gaps use the original published values and are rounded once; subtracting the rounded percentages can give a slightly different result.
- Establishments, year over year
- +12.9%State data coverage 100%
- Average weekly industry wage, year over year
- +0.8%State data coverage 100%
- Industry mix vintage
- EP-2025-2035
- BLS publication date
- Aug 28, 2026
- Source verification
- Verified against the committed source snapshotVerified Sep 17, 2026
- Canonical record URL
- https://jobmarkethealth.com/occupations/special-education-teachers-middle-school/california#evidence-record
- Derived by
- JobMarketHealth from BLS QCEW + published occupation industry mix
MethodologyBLS QCEWHow to citeQCEW state context release, 2026 Q1
AI & this occupation
How AI relates to Special education teachers, middle school work
Across 3 research exposure measures, Special education teachers, middle school is in the middle technical AI exposure band based on the mean of the available source-specific percentile ranks. Exposure describes how much of the work the studied AI capabilities could technically assist with; it is not a forecast of job loss.
Observed use of Claude for this occupation's tasks is in the higher third of occupations in the Anthropic Economic Index, a dated observed task-exposure benchmark, not conversation share or the share of workers using AI. Its observation window is not recorded in this saved release.
JobMarketHealth has not measured an AI effect on this occupation's employment or wages, and these figures do not enter its scores; there is no clear evidence of displacement in the data shown here.
Exposure measures (kept separate)
- GPTs are GPTs exposure (β, GPT-4 rated): 0.31 of 1, national percentile 48 (middle third)
- Microsoft AI applicability: 0.17 of 1, national percentile 58 (middle third)
- OECD AI Capability Gap (lower gap = higher potential exposure): gap 6.9 of 23, national percentile 8 (lower third)
OECD capability gap by domain
As published by the OECD: the gap between what the occupation demands (0-5) and current AI capability in each domain. A lower gap means AI is closer to the requirement (higher potential exposure); 0 means AI already meets it or the domain is not relevant.
- Language: gap 1.25 (demand 4.25 of 5)
- Social interaction: gap 2.25 (demand 4.25 of 5)
- Problem solving: gap 2.25 (demand 4.25 of 5)
- Creativity: gap 0.50 (demand 3.50 of 5)
- Metacognition & critical thinking: gap 2.25 (demand 4.25 of 5)
- Knowledge, learning & memory: gap 1.00 (demand 4.00 of 5)
- Vision: gap 0.00 (demand 2.60 of 5)
- Manipulation: gap 0.00 (demand 1.45 of 5)
- Robotic intelligence: gap 0.00 (demand 1.80 of 5)
National context: what businesses used generative AI for
From the Census 2025-26 BTOS AI Supplement (all industries; businesses whose employees used generative AI). Census did not measure Special education teachers, middle school specifically.
- Writing or editing documents, emails, or communications: 85.4%
- Searching for information or technical help: 49.9%
- Interpreting, analyzing, translating, or summarizing documents: 44.6%
- Information processing, paperwork, or filing: 34.7%
California context
In the Census BTOS core AI-use question, an estimated 24.6% of California employer businesses reported using AI in the two weeks ending 2026-10-04 (U.S.: 24.6%).
Separately, the one-time 2025-26 BTOS AI Supplement (collected 2025-11-17 to 2026-02-08) found 19.1% of California businesses using AI at that time, and 22.2% reporting that employees used generative AI for work tasks in the prior six months. It describes how AI was being used then, not a trend.
Using each occupation's exposure band and California employment weights (OEWS May 2025), 30.4% of covered jobs are in occupations in the higher-exposure band. This describes the state's occupation mix, not a measured AI effect.
Exposure and observed usage are separate measures and neither equals job loss. Census BTOS figures are business-level surveys and are not occupation-specific. Sources: GPTs are GPTs occupation exposure; Microsoft Working with AI: AI applicability; OECD AI Exposure Measure (AI Capability Gap); Anthropic Economic Index; Census BTOS Core AI Use; Census BTOS AI Supplement 2025-26. These figures do not affect Job Market Health scores. Explore AI & Jobs · How we use AI data.
How to read this page
QCEW measures employment and wages by industry, not by occupation. We weight those industry conditions using the published industry mix for Special education teachers, middle school. These figures describe the industries that employ Special education teachers, middle school; they are not direct counts of people working in the occupation or of jobs currently open. This page is not part of the national 0 to 100 Job Market Health score.
Source: BLS QCEW. See the methodology, the national Special education teachers, middle school report and about the data.
Related occupations
Compare California with other statesPublished industry employment, business locations and average weekly industry wages for up to three states, with the national benchmark in percentage points.
Special education teachers, middle school in other states
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