Equal Pay for Equal Work in California Community Colleges
By Scott Douglas, Southern California Regional Representative
- Introduction
- Why the Question Remains Unanswered
- Our Approach: Get the Data
- What Happened When We Tried
- What We Can Say Anyway
- What This Revealed
- The Proposal
- Scope and Limitations
- Conclusion
- Appendix A: District-Level Data
I. Introduction
The companion paper Nobody Ever Voted for This (CPFA, August 3, 2026) documents how the two-tier faculty compensation structure in the California Community College system emerged—not from legislative choice, but from a judicial misreading of a coherent statute and a recodification error that removed a compensation mandate, compounded by a half-century of failure to correct either. This paper treats that conclusion as established and asks what undoing it would cost.
The structure has two components: unequal pay, and the permanent-temporary classification that carries it. This paper costs the first, deliberately, because that is where the dollars are. Equalized pay is priced per FTEF regardless of classification, so eliminating permanent-temporary status adds little wage cost of its own: the same people teach the same classes at the same equalized rate—what changes is their status, not the price of their instruction (Section VIII). The largest later cost of a status correction would be health benefits—coverage the State already funds for this workforce through the Part-Time Faculty Health Insurance Program (Section VI); the remaining employer-side obligations fall within the categories this paper excludes and identifies as making the true cost higher (Section V). Costing the elimination of the two-tier structure is therefore, in substance, costing the pay.
This paper does three things. It estimates a floor from available public data; it demonstrates why a precise estimate is impossible under the current reporting architecture; and it shows what makes it possible—a reporting pathway, built from data districts already collect, proposed in Section VII. The impossibility is this paper’s primary finding. The pathway is its remedy.
The answer should be a computation, not a research project. Districts pay people. The cost of paying them at one rate for the same unit of work is knowable from what districts already record. That it has not been computed is itself a finding about the state’s informational infrastructure.
A note on terminology. As used here, “pro rata” means the per-FTEF cost of instruction, applied uniformly regardless of employment classification. Teaching a fraction of a full load is not a tier; being paid a different rate for it is.
II. Why the Question Remains Unanswered
Nobody Ever Voted for This demonstrates that the Legislature never created distinct faculty classifications as a compensation policy. This paper proceeds from that finding. The question is not how to calibrate the gap between tiers. It is what eliminating the gap would cost. Prior approaches that define “parity” as a percentage of full-time compensation—however generous—accept the premise that two tiers should exist and optimize within that structure. That is not what is being considered here.
This reframing has both a methodological and a conceptual dimension.
The methodological problem. Prior estimates have been built from salary schedule comparisons. The California Federation of Teachers publishes an annual Part-Time Faculty Salary Comparison that reports salary schedule rates at specific steps for all 72 districts.¹ The methodology applies a 0.75 “non-teaching” multiplier that reduces the comparison rate by 25% before the gap is measured. A statewide cost estimate built from these schedule rates additionally requires assumptions about where the workforce sits on those schedules—assumptions that cannot be verified because districts do not publish step-placement distributions for part-time faculty. Some districts have 15 steps; others have 5. Some have longevity bumps; others do not. Schedule comparisons capture the structure of the inequity but not its magnitude.
AB 1269 (Garcia, 2021), co-sponsored by the Community College Association and the California Federation of Teachers, proposed a different path: commissioning the Chancellor’s Office to conduct a comprehensive study of part-time faculty compensation. Legislative efforts of this kind go back decades—AB 420 (Wildman, 1999) directed a comprehensive CPEC study; AB 1269 sought another and died in Appropriations. Neither produced durable reform.
The conceptual problem. Every prior approach defines the question in terms that preserve the structure Nobody Ever Voted for This documents as accidental. The multiplier described above has no legal basis—former Education Code § 13503.1 required pro-rata compensation for part-time certificated employees, and no statute, regulation, or judicial decision authorizes a two-tier compensation structure.
The assumption underlying the multiplier—that non-teaching obligations justify a rate discount—is structurally backwards. Non-teaching obligations—committee service, governance, curriculum development—are properly handled through workload models such as release time or stipends that apply equally to all faculty. Under either model, the instructional rate is untouched. With release time, a faculty member who serves on committees teaches fewer sections; the rate per section does not change. With stipends, service work is compensated separately at the same rate for everyone. No multiplier is needed because no discount is applied.
Any definition of “parity” that produces a different price per FTEF by employment classification—regardless of the percentage—assumes two tiers should exist and adjusts the distance between them. The single tier comes first. If the system then wants to revisit how non-teaching work is allocated and compensated, that conversation happens after equalization and applies to everyone equally.
(The companion Legislative Brief develops an enforcement mechanism that depends on this single-tier framing.)
Two compounding technical errors in prior estimates. Beyond the conceptual problem, prior schedule-based estimates understated the cost for identifiable technical reasons. First, they generally used an approximate statewide part-time FTEF figure of around 10,000. The actual figure from the Fall 2023 FON compliance report is 12,520.8—25% higher. This alone scales any schedule-based estimate upward by a quarter. Second, schedule-based estimates measure only the part-time teaching gap. They do not capture the additional cost of equalizing overload and summer instruction, which are paid at discounted rates and represent a substantial share of total non-regular instructional expenditure. These errors compound multiplicatively against the 0.75 multiplier: the result is a fraction of the actual cost.
III. Our Approach: Get the Data
We did not propose a study. We assumed that the public record—documents filed annually by every district—contained sufficient granularity to compute the cost of equalization directly. Three publicly available documents per district, paired to the same fiscal year, should in principle provide the data—and, as Section IV shows, in practice do not:
The 50% Law Report (ECS 84362). Filed annually by every district with the Chancellor’s Office. Reports unrestricted general fund expenditures by object code, including Objects 1300 (other instructional salaries—part-time teaching, overload, summer, stipends) and 1400 (other non-instructional academic salaries).² Their sum gives total non-regular academic payroll.
The CCFS-311 Annual Financial and Budget Report, Table V (Fund 10 Combined). Reports total academic salaries (Object 1000—regular plus non-regular combined) across all funds.
The Full-Time Faculty Obligation (FON) Compliance Report. Published annually by the Chancellor’s Office, reporting regular FTEF per Title 5 § 53309 and part-time FTEF per Title 5 § 53310 for every district.
The method is simple arithmetic. Non-regular payroll is observed directly from the 50% Law Report. Regular payroll is derived by subtracting non-regular payroll from the Table V total. Each pool is divided by its corresponding FTEF from the FON. The difference between the two per-FTEF rates, multiplied by statewide part-time FTEF, gives the cost of equalization.
Gap/FTEF = (Regular Payroll / Regular FTEF) − (Non-Regular Payroll / Part-Time FTEF)
Equalization Cost = Gap/FTEF × Statewide Part-Time FTEF (12,520.8)
These two equations are the entire method. The gap—the additional cost per FTEF needed to equalize non-regular instruction—is the quantity this paper attempts to measure. No salary schedule assumptions. No workforce distribution guesses. No non-teaching multiplier. If the reporting system contained what it should, this would have produced an exact answer for all 72 districts.³ To test this assumption, we applied the method to 13 districts as a proof of concept.
IV. What Happened When We Tried
We attempted 13 districts, selected for geographic and structural diversity: large urban, large suburban, mid-size, small, coastal, inland, Central Valley, basic aid, and apportionment-funded. Two immediately produced results so distorted that the gap inverted to negative—the first indication that the reporting architecture could not support the computation. The remaining eleven produced results that appeared reasonable. Nothing suggested the data was inaccurate—the problem was that the reporting categories did not contain what their labels suggested. Object 1300, for example, is titled “other instructional salaries,” but it combines part-time base pay, full-time overload, summer instruction, and stipends into a single undifferentiated total—and for several of these components, there is no corresponding FTEF reported in the FON report, so an accurate average pay rate per FTEF could not be computed. As the analysis proceeded, this structural mismatch proved present in every district.
The mismatch is written into the FTEF regulations. Title 5 § 53309(d) excludes full-time faculty overload from the FTEF calculation entirely: overload pay sits in Object 1300, but the workload appears in neither FTEF count. Sections 53309(a) and 53310(a) exclude noncredit instructional assignments from both FTEF counts, so noncredit taught by part-time faculty or as overload adds Object 1300 dollars with no FTEF counterpart. Section 53310(c) excludes the FTEF of part-time faculty who replace full-time faculty on sabbatical, released or reassigned time, unpaid leave, or late resignation or retirement, and of those funded from temporary local sources—though their salaries are ordinary temporary-instructor pay within Object 1300; sections 53309(e)–(i) meanwhile count the absent full-timer as full FTEF, in the unpaid-leave and late-retirement cases with no matching salary, deflating the regular rate as well. Stipends carry dollars with no hours-based FTEF at all. And the FON reports fall-term FTEF, so summer and intersession compensation has no denominator counterpart. Each of these adds dollars to a numerator and nothing to its denominator—or FTEF to a denominator and nothing to its numerator—and every one of them compresses the measured gap.
These exclusions are not sloppiness. The FTEF definitions were built to measure hiring compliance, deliberately stripping out everything that is not a countable hire—which is precisely why they fail as payroll denominators. At districts with small non-regular FTEF pools dominated by expensive overload, the distortion is extreme enough to invert the result entirely—producing a negative gap that is absurd as a pay comparison but inevitable as arithmetic.
One regulatory exclusion runs the other way: because § 53309(a) removes noncredit from full-time FTEF, in-load noncredit taught by contract faculty inflates regular cost per FTEF and enlarges the measured gap—a district-dependent effect, concentrated where noncredit programs are staffed with regular faculty. Together with the fund-scope mismatch between the data sources, these are the identifiable upward pressures. Both are narrower in reach than the downward distortions, which operate on every district’s overload, summer, and part-time instruction, and they do not offset them. The identifiable distortions predominantly bias the estimate downward, supporting its treatment as a conservative floor.
We stopped not because 13 was a sufficient sample but because the problems made clear that completing all 72 districts this way was the wrong path. The path is fixing why it is this hard in the first place.
V. What We Can Say Anyway
Across the 13 districts attempted, the method produced a weighted mean gap of $33,717 per FTEF. District-level results ranged from large positive gaps to two inversions where structural distortion was extreme enough to flip the sign. All results, including inversions, are included in the computation. The full district-level data appears in Appendix A.
Applied to statewide part-time FTEF of 12,520.8, this yields an exploratory floor of approximately $422 million per year—roughly 4.5% of current state appropriations to the system (Proposition 98 General Fund plus other state funds, $9.45 billion in FY 2023–24). Prior estimates were substantially lower for the compounding reasons analyzed in Section II.
The thirteen districts were selected purposively for structural and geographic diversity, not randomly, and extrapolation from a purposive sample carries selection error that this method cannot bound. The figure is accordingly an indication of scale, not a point estimate. Its claim to being a floor rests not on the sample but on the direction of the identifiable distortions and exclusions, assembled below.
Why the figure is a floor. Two distortions operate inside the computation, and both push it downward. First, the numerator–denominator mismatches documented in Section IV—overload, part-time noncredit, replacement assignments, stipends, and summer and intersession pay, each contributing Object 1300 dollars with no FTEF counterpart, alongside leave and late-retirement FTEF counted with no matching salary—compress the measured gap in every district. Second, the two sign-inverted districts—where that mismatch is at its most extreme—are retained in the weighted mean. Excluding them raises the weighted mean gap to approximately $43,100 per FTEF and the statewide figure to approximately $540 million; their inclusion depresses the estimate by roughly $118 million. They are retained because the method, not the districts, produced the inversions—but the delta measures, from within the sample itself, the downward force of the distortion the whole sample suffers in lesser degree.
Two exclusions then operate outside the computation, and both mean the full cost of equalization exceeds any figure computed here: employer-side payroll obligations on the equalized salary base (below), and the unmeasured noncredit pay gap (Section VIII). Two identifiable effects run upward: the fund-scope mismatch that slightly inflates regular cost per FTEF (Section IV), and the regular-side noncredit exclusion of § 53309(a), concentrated in districts that staff noncredit programs with regular faculty. Noncredit thus distorts in both directions, and its net cannot be determined from public reports—while its unmeasured gap remains an additional cost beyond any figure here regardless. The upward effects are narrower in reach than the downward ones, which operate on every district’s overload, summer, and part-time instruction, and do not offset them. That is the basis on which $422 million is stated as a floor rather than an estimate.
The sources of understatement cannot be quantified because the data needed—the decomposition of Object 1300 and the corresponding FTEF for summer and overload—is not available in public reports. The floor is understated by an unknown but potentially substantial margin.
Employer-side payroll costs are also excluded. Equalization of non-regular salaries triggers increased employer contributions—including CalSTRS or alternative retirement plan obligations and Medicare—but the effective rate varies by component and cannot be determined from the salary data used in this analysis. The proposal in Section VII resolves this.
VI. What This Revealed
The data needed to answer the cost question exists. Every district produces individual-level compensation data every pay period: who was paid, how much, for what assignment, under what classification, and where the money went. That data is transmitted to CalSTRS for retirement contribution calculations. It is aggregated into object codes for the Chancellor’s Office via the CCFS-311. It is counted as FTEF for the FON. Each reporting channel strips out what the others need.
This is not a data collection failure. It is a reporting architecture problem.
The architecture was built to monitor categorical programs—the parity fund, the office hours supplement, the health insurance program. Each legislative intervention generated its own reporting line. Over time, those requirements became the architecture. The CCFS-311 tracks budget compliance. The 50% Law Report tracks the instructional expenditure ratio. The FON tracks the full-time hiring obligation. CalSTRS tracks retirement contributions.
The result is a system that can tell you whether a specific program’s allocation was spent. It cannot tell you whether the underlying compensation disparity is growing or shrinking. It cannot measure its own compensation structure.
This paper’s investigation did not fail because the method was wrong. The method is arithmetic—four numbers per district, two equations. It hit a ceiling imposed by an architecture that destroys the granularity the question requires before the data reaches the public record. The problems documented in Section IV are not data quality issues. They are design consequences of a reporting system built to track the band-aids rather than measure the wound.
VII. The Proposal
The state does not need another study. It does not need a working group to define parity. It needs to stop fragmenting data it already collects.
Districts already produce every data element needed at the individual level. The proposal is a reporting pathway that preserves that granularity and makes it available—with appropriate privacy protections—to the Chancellor’s Office, the Legislature, and CalSTRS as consumers of a shared state resource rather than proprietors of separate silos.
Required data elements. At minimum, the reporting extract must preserve the following fields per individual, per pay period—all of which districts already maintain in their payroll systems:
System-wide faculty identifier, consistent across districts and state agencies, to enable cross-district tracking of compensation and workload
District
Employment classification (regular, adjunct, temporary)
Assignment type (base contract, overload, summer, intersession, stipend)
FTEF associated with the assignment
Compensation amount
CalSTRS crediting treatment (DB-creditable, DBS-routed, non-creditable)
The Chancellor’s Office has already established a system-wide identifier—the CCCID—that tracks students across districts. No equivalent exists for faculty. The infrastructure concept is proven; only the extension is missing.
The last field—CalSTRS crediting treatment—is also critical. Districts already track it because CalSTRS requires it for contribution calculations. Preserving it in the reporting extract means the total fiscal cost of equalization—salary plus employer-side obligations—becomes a computation at current contribution rates, not an estimate requiring assumptions about the composition of Object 1300.
Privacy protections. Aggregation thresholds, suppression rules for small cells, and restriction of individual-level access to authorized oversight functions are standard for interagency data sharing and do not require novel solutions.
Implementation realism. This paper does not minimize the challenge. Seventy-three districts use different payroll systems, different HR classification structures, and different reporting workflows. Standardizing the extract across all 73 is real work. Nor has this paper verified exactly what the CalSTRS employer reporting extract currently contains versus what the equity question requires. That gap is verifiable and should be verified before legislation is drafted.
What can be said with confidence: the information exists, is already generated by every district, and is currently fragmented by a reporting architecture designed for a different purpose. The cost of equalization is knowable.
Independent value. The data improvements proposed here serve purposes beyond equalization. FON compliance verification, 50% Law accuracy, workforce planning, and budget transparency all depend on the same granularity the current architecture discards. The proposal has independent value regardless of whether equalization is pursued.
Relationship to the Legislative Brief. The specific legislative mechanism for achieving equalization—a conditional exemption framework under Labor Code § 515.7, with transitional safe harbor and sunset provisions—is developed in the companion Legislative Brief. This paper establishes the scale, diagnoses the data problem, and proposes the informational infrastructure. The Brief carries the policy action. The reader should understand that the $422 million figure is a floor, not a point estimate, and that the true cost is higher and not precisely quantifiable under the current reporting architecture.
VIII. Scope and Limitations
The estimate assumes the current volume and distribution of non-regular instruction holds constant under equalization. In practice, districts would likely adjust scheduling, reduce overload assignments, or convert some part-time positions to full-time. The estimate measures the current gap, not the equilibrium cost of a reformed system. The primary behavioral response—shifting toward full-time positions—does not reduce total per-FTEF compensation under equalization; it changes who delivers the instruction, not what it costs per unit.
Noncredit instruction, which may represent a substantial additional pay gap at some districts, is not measured here—though it participates in the Section IV distortions from both directions: noncredit taught by part-time faculty or as overload adds Object 1300 dollars with no FTEF counterpart, while in-load noncredit taught by contract faculty adds regular-payroll dollars with no regular FTEF (Cal. Code Regs., tit. 5, §§ 53309(a), 53310(a)). Its compensation structures, workload definitions, and reporting frameworks differ from credit instruction in ways this methodology does not attempt to resolve.
This paper investigates one question and in doing so reveals why it has never been precisely answered.
IX. Conclusion
The cost of equalization is knowable. Every district already records, each pay period, who was paid, how much, for which assignment, and under which classification. The figure has never been computed because the state’s reporting infrastructure was built to monitor individual programs rather than measure systemic compensation equity—that is this paper’s primary finding. Fixing that infrastructure is the prerequisite for a precise answer and for any durable equalization mechanism, because without it, no one can verify whether the solution is working.
What the exploratory computation establishes is the scale. The two-tier structure documented in Nobody Ever Voted for This costs at least $422 million per year in wage disparity in credit instruction alone—a floor, for the reasons assembled in Section V, and likely substantially more.
Appendix A: District-Level Data
All figures FY 2023–24. Objects 1300 and 1400 from the 50% Law Report (Total column, unrestricted general fund). Table V Object 1000 from CCFS-311 Fund 10 Combined (Actual). FTEF from the FON Compliance Report (Fall 2023). Non-regular payroll = Objects 1300 + 1400. Regular payroll = Table V − Non-reg payroll.
Table A1. Source Data (n = 13)
| District | Obj 1300 | Obj 1400 | Table V Obj 1000 | Reg FTEF | NR FTEF |
|---|---|---|---|---|---|
| LACCD | $138,673,703 | $7,747,834 | $441,314,317 | 1,573.1 | 880.6 |
| Los Rios | $54,977,478 | $3,323,980 | $200,788,924 | 894.9 | 480.1 |
| San Diego | $52,509,504 | $1,916,878 | $157,178,624 | 573.1 | 493.7 |
| Mt. San Antonio | $47,643,908 | $3,357,201 | $131,561,939 | 449.0 | 366.0 |
| Kern | $17,934,817 | $1,965,682 | $89,753,377 | 502.0 | 263.0 |
| San Jose-Evergreen | $24,370,938 | $1,495,573 | $68,690,401 | 236.9 | 155.2 |
| Allan Hancock | $9,355,154 | $1,292,435 | $31,719,160 | 162.2 | 128.3 |
| Riverside | $48,693,571 | $2,548,643 | $141,913,728 | 483.6 | 350.3 |
| State Center | $27,841,221 | $4,996,504 | $148,643,929 | 664.8 | 404.5 |
| Ventura | $34,432,884 | $1,386,708 | $95,465,937 | 438.8 | 285.5 |
| Southwestern | $22,775,798 | $1,735,029 | $65,452,576 | 292.6 | 238.7 |
| Foothill-DeAnza | $40,241,500 | $890,685 | $108,602,832 | 404.0 | 135.3 |
| Sonoma County | $21,672,493 | $1,912,571 | $69,073,962 | 310.7 | 77.2 |
Table A2. Computed Results (n = 13)
| District | Reg $/FTEF | NR $/FTEF | Gap/FTEF | NR FTEF | Cost to Eq. | Region |
|---|---|---|---|---|---|---|
| LACCD | $187,460 | $166,275 | $21,185 | 880.6 | $18,655,433 | Large urban |
| Los Rios | $159,222 | $121,436 | $37,786 | 480.1 | $18,140,862 | Large suburban |
| San Diego | $179,292 | $110,242 | $69,050 | 493.7 | $34,090,076 | Large urban |
| Mt. San Antonio | $179,423 | $139,347 | $40,075 | 366.0 | $14,667,630 | Large suburban |
| Kern | $139,149 | $75,668 | $63,481 | 263.0 | $16,695,503 | Central Valley |
| San Jose-Evergreen | $180,768 | $166,665 | $14,103 | 155.2 | $2,189,186 | Bay Area |
| Allan Hancock | $129,911 | $82,989 | $46,922 | 128.3 | $6,020,293 | Central Coast |
| Riverside | $187,493 | $146,281 | $41,212 | 350.3 | $14,436,564 | Inland Empire |
| State Center | $174,197 | $81,181 | $93,016 | 404.5 | $37,624,972 | Central Valley |
| Ventura | $135,931 | $125,463 | $10,468 | 285.5 | $2,988,614 | Coastal SoCal |
| Southwestern | $139,924 | $102,684 | $37,240 | 238.7 | $8,893,188 | South Bay |
| Foothill-DeAnza | $167,007 | $304,007 | −$137,001 | 135.3 | −$18,536,235 | Bay Area |
| Sonoma County | $146,408 | $305,506 | −$159,098 | 77.2 | −$12,282,366 | North Bay |
| Wtd Mean | $33,717 | 4,258.4 | $143,583,720 | Sum |
Notes. San Jose-Evergreen is a basic aid district. Allan Hancock has $701,726 in Objects 1300/1400 in the Excluded Activities column (AC 6800–7390); Total column used consistently across all districts. Excluding the two sign-inverted districts (Foothill-DeAnza, Sonoma County): sum $174,402,321 over 4,045.9 NR FTEF = $43,106 per FTEF; × 12,520.8 statewide part-time FTEF ≈ $539.7 million.
Statewide Totals (FON Fall 2023). Part-time FTEF (Column d, per Title 5 § 53310): 12,520.8. Regular FTEF: 19,051.3. Total FTEF: 31,572.1. Regular percentage: 60%.
Appendix B: Data Sources and URLs
FON Compliance Report (Fall 2023): California Community Colleges Chancellor’s Office, “Fall 2023 Full-Time Faculty Obligation Compliance and Percentage,” dated November 9, 2023.
50% Law Reports and CCFS-311 Annual Reports: Filed by each district with the Chancellor’s Office. Available through district websites (Business/Financial Affairs or Budget & Financial Reports pages) and the Chancellor’s Office Reporting Portal.
Budget and Accounting Manual: California Community Colleges Chancellor’s Office, Budget and Accounting Manual, 2012 edition (effective July 9, 2012 – November 18, 2024; governing FY 2023–24 reporting), Chapter 4, Classification of Expenditures by Object (Objects 1100, 1300, 1400). The 2024 edition (effective November 2024) and the Chancellor’s Office 50% Law compliance guidance carry the same definitions.
Title 5 FTEF regulations: California Code of Regulations, title 5, § 53309 (rules for calculating FTEF attributable to full-time faculty) and § 53310 (rules for calculating FTEF attributable to part-time faculty). Cited in Sections IV, V, and VIII.
CFT Part-Time Faculty Salary Comparison: California Federation of Teachers, Part-Time Faculty Salary Comparisons 2024–25. Used for cross-reference in Section II.
AB 1269 (Garcia, 2021): Assembly Bill 1269, 2021–22 Regular Session. Committee analysis available through the Assembly Committee on Higher Education.
State appropriations figure: Legislative Analyst’s Office, “California Community Colleges Funding by Source,” January 2024 (EdBudget). Revised 2023–24 figures: Proposition 98 General Fund $8,425 million plus Other State funds $1,025 million = $9,450 million in state appropriations. (Total funding from all sources, including local property tax, enrollment fees, other local revenue, and federal funds, was $17,869 million.)
Endnotes
Calbright College does not appear in the FON Compliance Report: noncredit instruction is excluded from FON calculations, and Calbright offers only noncredit instruction. The computation universe is therefore the 72 districts common to all three data sources.
The California Community College system comprises 73 districts, including Calbright College, the statewide online, noncredit-only district. Counts of 72 in this paper denote populations from which Calbright is absent, as noted where used.
California Community Colleges Budget and Accounting Manual, ch. 4, Classification of Expenditures by Object: Object 1300, Instructional Salaries, Other, comprises salaries of instructors not designated as contract or regular employees, expressly including temporary-instructor salaries under Education Code § 87477 and “overload and stipend pay for instructors designated as contract employees or as regular employees.” The definition of Object 1100 (Instructional Salaries, Contract or Regular Status) contains the corresponding routing sentence directing overload and stipend pay of contract or regular instructors out of that account and into Objects 1300 or 1400. Object 1400, Noninstructional Salaries, Other, comprises salaries of noninstructional academic employees not designated as contract or regular, including faculty stipends for noninstructional work. Summer-session instruction is not enumerated but falls within these accounts by operation of the definitions, being compensated outside contract or regular status. FY 2023–24 reporting was governed by the 2012 edition (effective July 9, 2012 – November 18, 2024); the definitions appear identically in the 2024 edition and in the Chancellor’s Office 50% Law compliance guidance. Districts are required to adhere to the BAM by Education Code § 84030; the manual is authorized by California Code of Regulations, title 5, § 59010.