The likelihood of being identified as at risk increases as historically underserved background characteristics intersect, with variation by gender and race/ethnicity, and school characteristics also matter¶
Claim · All claims
Evidence · 1 study (3 entries) · associationalr2–r3·q2
Currency · newest study 2024 · checked against its sources 2026-10-20 (automated, 3 of 3 entries) · not reviewed by a person · recheck by 2027: tool and model accuracy changes quickly
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? Students belonging to more historically underserved groups have a greater chance of being identified as at risk; students in all three groups have an even higher likelihood. → Mariann Lemke 2024
q2 i? The increase varies by gender and background: female English learners and special education students are more likely to be identified than males across ethnoracial groups; Asian students show the smallest increases. → Mariann Lemke 2024 (2)
q2 i? Students in schools with above-average low income percentages, below-average teacher retention, and below-average attendance have a higher likelihood of significant risk. → Mariann Lemke 2024 (3)
Evidence¶
Mariann Lemke 2024¶
Mariann Lemke, Dan Murphy, Aaron Soo Ping Chow, and Angela Acuña. (2024). Early Literacy Performance in Massachusetts: Results of Ongoing Analysis of Literacy Screening Assessments. WestEd. https://eric.ed.gov/?id=ED663754
q2 · i? · associational · r2
New intersectional analysis examining students' overlapping social and economic background characteristics in combination, using a statistical model described in the report's appendix.
"students who receive special education or English learner support services and come from a low income background have a greater likelihood of being identified as at risk than do students with only one of these characteristics. And students belonging to all three groups have an even higher likelihood of being identified as at risk."
Mariann Lemke 2024 (2)¶
Mariann Lemke, Dan Murphy, Aaron Soo Ping Chow, and Angela Acuña. (2024). Early Literacy Performance in Massachusetts: Results of Ongoing Analysis of Literacy Screening Assessments. WestEd. https://eric.ed.gov/?id=ED663754
q2 · i? · associational · r2
The intersectional analysis finds the pattern of increasing risk with intersecting characteristics holds for all students, but the size of the increase varies by gender and other background factors.
"Female students who are English learners or who receive special education services are more likely to be identified as at risk than males across ethnoracial groups. Asian students show the smallest increases in likelihood of being identified as at risk across ethnoracial groups."
Mariann Lemke 2024 (3)¶
Mariann Lemke, Dan Murphy, Aaron Soo Ping Chow, and Angela Acuña. (2024). Early Literacy Performance in Massachusetts: Results of Ongoing Analysis of Literacy Screening Assessments. WestEd. https://eric.ed.gov/?id=ED663754
q2 · i? · associational · r3
School-level characteristics were included in the likelihood analysis; the report notes that in Massachusetts more Black and Hispanic students attend schools with these characteristics.
"Students in schools with above-average percentages of low income students, below-average teacher retention rates, and below-average student attendance have a higher likelihood of being identified as at significant risk."
Discussion¶
Related Claims¶
- The likelihood of being identified as significantly below benchmark in early literacy screening increases as historically underserved background characteristics intersect — possibly the same claim (merge candidate)
- School and district factors relate to risk identification: low income concentration correlates with repeated risk identification, and segregation modestly increases it, though some schools outperform model predictions — related
- School characteristics—percentage of low income students, teacher retention, and attendance—are associated with students' likelihood of being identified as at significant risk in early literacy screening — related
- Students from low income, English learner, special education, and several racial/ethnic groups are more likely to be repeatedly identified as significantly below benchmark, with low income students 2.5 times as likely — related
- School-level concentration of low income students and racial isolation are associated with higher early literacy risk rates — related
- Low income, English learner, special education, Black, and Hispanic students were more likely to be classified significantly below benchmark at each time period and more than once — related
- Students from low income backgrounds, English learners, students receiving special education services, and Black and Hispanic students were more often identified as at significant risk — related
- Students' risk of suspension is more strongly determined by which school they attend than by their individual backgrounds — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
intersectional-risk-likelihood |
title |
The likelihood of being identified as at risk increases as historically underserved background characteristics intersect, with variation by gender and race/ethnicity, and school characteristics also matter |
description |
The likelihood of being identified as at risk increases as historically underserved background characteristics intersect, with variation by gender and race/ethnicity, and school characteristics also matter |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2024 |
source_checked |
2026-10-20 |
recheck_by |
2027 |
generated |
by process:wiki-ingest on 2026-10-09 |
trust |
unverified — no one has confirmed this page's content |
sources |
3 — mariann-lemke-2024, mariann-lemke-2024-2, mariann-lemke-2024-3 |
Frontmatter is the page's machine-readable record — see the Schema & Guide.