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Published research

How much does a school filter actually block?

Every filtering policy removes more than it intends to. We simulated five stylised policies over 103,367,510 categorised domains from our register to measure exactly what each one blocks — and how much education, health, government, news, science and civic content goes with it.

103.4Mcategorised domains simulated
5stylised filtering policies
57categories in the co-occurrence matrix
16.3Mprotected domains measured
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The paper

Peer review is still ahead of it; the working paper is open on SSRN and free to read and cite.

Where Over-Blocking Comes From: Simulating CIPA School Filtering Policies on 103 Million Categorised Domains

Every filtering policy removes more than the law requires. This paper measures how much more, by simulating five stylised policies over WebFilteringDatabase’s full register of categorised domains and counting exactly which education, health, government, news, science and civic domains each one takes with it.

Samo Plibersek · 11 pages · SSRN working paper · https://doi.org/10.2139/ssrn.7638439

Read on SSRN Author page

What it found

Blocking the categories the statute actually names costs almost nothing in legitimate content. The cost appears when a policy grows past that core.

0.92%of domains blocked by the statutory coreThe Adult category alone — the one matching the three content classes CIPA names.
0.048%of protected domains caught by that coreEducation, health, government, news, science and civic domains. Over-blocking is near zero here.
4.59%blocked by a typical 17-category policy0.30% of protected domains go with it.
19.1%blocked by a restrictive 29-category policy7.6% of protected domains — 1,236,688 of them, twenty-six times the typical policy.

Policy by policy

“Protected” means a domain carrying an education, health, government, news, science or civic label — 16,250,357 of the 103,367,510 domains. The last column is over-blocking relative to the statutory core.

PolicyCategories blockedDomains blocked Protected domains blockedvs statutory core
Statutory core1 category (Adult)0.92%0.048%—
Conservative9 categories2.41%0.11%2.3×
Typical district17 categories4.59%0.30%6.3×
Strict23 categories11.4%2.9%60×
Restrictive29 categories19.1%7.6%158×

Each policy is computed under three rules for domains carrying several labels, which 9.0% of them do. The paper reports all three; the figures above use the middle rule.

The dataset

Aggregate counts only, with no domain names: category prevalence by link-authority band, the full 57 × 57 co-occurrence matrix and pair statistics, policy simulations by rule, domain class and popularity, a cost-ordered blocking curve, the co-label context of sensitive categories, and shares by country and domain suffix. A codebook defines every term. Released under CC BY 4.0 and deposited in five repositories.

FigshareDataset package
IEEE DataPortDataset package
Mendeley DataDataset package
OSFDataset package
ZenodoDataset package

Repository DOIs are added here as each deposit is minted. Until then, cite the SSRN paper.

Cite this work

Samo Plibersek (2026). Where Over-Blocking Comes From: Simulating CIPA School Filtering Policies on 103 Million Categorised Domains. SSRN Working Paper. https://doi.org/10.2139/ssrn.7638439

For journalists and researchers

Every figure in the paper is an aggregate; no individual domain is named. The text and the dataset are CC BY 4.0, so both can be quoted, charted and redistributed with attribution. For the methodology, a custom cut of the data or comment, get in touch. Our 49,000-domain research dataset is a free sample of the register the paper is built on.