BC schools are failing disabled students: an absence analysis

This analysis is based on a provincial FOI request to the BC Ministry of Education, file ECC-2025-52461, which was shared recently, bc BCEdAccess.

The data covers absence rates, absence reasons, enrolment, and mid-year exits for BC public school students, broken down by inclusive education designation, across the 2022/23 and 2023/24 school years. This analysis focuses on district-wide absence rates and reason codes, cross-referenced with school size and demographic information from the Ministry’s published student enrolment data.

• In every single BC school district, children with disabilities are absent at higher rates than their non-disabled peers.
• Nisga’a District: 48% median absence for designated students. Stikine District: 35%.
• Behaviour-designated students: 43% of all formally recorded suspension absence — from a group representing a small fraction of the total student population.
• The Vancouver School Board told CBC that 99% of students attend every day. Their own data, extracted through FOI, shows disabled students in Vancouver absent 16% of the time.

An absence epidemic

Every parent I have spoken to has kept their disabled child home, at some point, because the support that was supposed to be in place was not there: the EA who was never scheduled despite seven previous years of requiring one, the behaviour support plan that existed on paper only, the slow erosion of a child’s health and willingness to attend across months of withdrawn support.

Sometimes the trigger is acute — the EA called in sick and no replacement was arranged, the substitute teacher has no context, the schedule changed and nobody thought to warn a child who needs preparation.

More often it is the accumulated weight of a system which never adequately supported this child and the family’s hard-won knowledge of exactly how much their child can absorb before the cost becomes too high.

When CBC journalist Tara Carman began writing a series on student absences, such as Absences increasing in B.C.’s biggest school districts, my first thought was: wait until you find out how many of those absences belong to disabled children.

Carman’s reporting named learning differences as a contributing factor and included the story of a Burnaby mother whose autistic son spent increasingly less time in school after supports failed to meet his needs. The Vancouver School Board’s response was:

“Ninety-nine per cent of our students attend in the VSB every single day and I think the numbers that you see, the data that you’ve collected from us, doesn’t tell that whole story.. It’s less than one per cent of our students who actually have an attendance challenge.” 

– Maureen McRae-Stanger, Associate Superintendent, Vancouver School Board (VSB)

McRae-Stanger did not specify which year or metric she was referring to. The Ministry shows a median of 91% of non-designated students and 87% of designated students attended on a given day in Vancouver in the years 2022-2024.

Whether VSB attendance improved dramatically in 2024/25 is a question the Ministry’s data will eventually answer — but the claim that less than 1% of students have an attendance challenge is difficult to reconcile with the pattern this analysis documents.

Absence by district by designation

Below you can see the median absence rate for each school district for children who do not have a special designation and for children who do. Note: we’re looking at standard public schools here, not private or alternative schools.

District	No Designation	Has Designation	Difference
Southeast Kootenay	13%	18%	4%
Rocky Mountain	14%	17%	3%
Kootenay Lake	16%	20%	4%
Arrow Lakes	17%	16%	-1%
Revelstoke	11%	12%	1%
Kootenay-Columbia	13%	17%	4%
Vernon	14%	19%	5%
Central Okanagan	13%	16%	3%
Cariboo-Chilcotin	17%	17%	0%
Quesnel	20%	21%	2%
Chilliwack	14%	18%	5%
Abbotsford	13%	18%	5%
Langley	13%	17%	4%
Surrey	11%	14%	3%
Delta	11%	16%	5%
Richmond	8%	10%	2%
Vancouver	9%	13%	4%
New Westminster	10%	15%	5%
Burnaby	9%	11%	3%
Maple Ridge-Pitt Meadows	10%	13%	2%
Coquitlam	11%	14%	3%
North Vancouver	9%	12%	3%
West Vancouver	11%	14%	4%
Sunshine Coast	15%	19%	4%
Powell River	16%	18%	2%
Sea to Sky	14%	19%	5%
Central Coast	25%	31%	6%
Haida Gwaii	19%	21%	2%
Boundary	14%	20%	7%
Prince Rupert	21%	29%	8%
Okanagan Similkameen	14%	16%	3%
Bulkley Valley	18%	22%	4%
Prince George	16%	20%	4%
Nicola-Similkameen	15%	19%	4%
Peace River South	17%	21%	5%
Peace River North	15%	16%	1%
Greater Victoria	13%	16%	3%
Sooke	11%	14%	3%
Saanich	13%	17%	3%
Gulf Islands	14%	14%	0%
Okanagan Skaha	13%	18%	5%
Nanaimo-Ladysmith	13%	18%	5%
Qualicum	14%	17%	3%
Alberni	17%	16%	-1%
Comox Valley	12%	14%	2%
Campbell River	17%	23%	5%
Kamloops/Thompson	15%	18%	3%
Gold Trail	20%	25%	5%
Mission	13%	16%	3%
Fraser-Cascade	20%	27%	7%
Cowichan Valley	16%	22%	6%
Fort Nelson	16%	21%	5%
Coast Mountains	18%	23%	5%
North Okanagan-Shuswap	14%	18%	5%
Vancouver Island West	24%	23%	-2%
Vancouver Island North	18%	25%	7%
Stikine	30%	35%	5%
Nechako Lakes	19%	22%	3%
Nisga’a	30%	48%	18%
Conseil scolaire francophone	9%	9%	0%

Source table

A note on how these figures are calculated

Throughout this analysis we use the median rather than the average to summarise absence rates. The average adds all values together and divides by the number of schools — which means a single school with an unusually high or low rate can pull the figure significantly in either direction. The median is simply the middle value when all schools are ranked from lowest to highest, meaning half of schools fall above it and half below. For data like this — where a small number of schools show extreme absence rates that could distort the overall picture — the median gives a more accurate sense of what a typical school actually looks like.

When we say the median absence rate for designated students in Nisga’a is 48%, we mean that half of the school-designation combinations in that district show absence rates above 48% and half below. The true situation for some individual schools is worse. In Stikine, one school records an absence rate of 40% for non-designated students and 89% for designated students — the same community, the same building, a 49-point gap that makes visible in a single school what this analysis documents across the province. School by school analysis will be published in a follow up post.

Districts with most absence for student with designations

Some districts have substantially higher rates of absence by children with designations than others. 

District	No designation	Has designation	Difference
Nisga’a	30%	48%	18%
Stikine	30%	35%	5%
Central Coast	25%	31%	6%
Prince Rupert	21%	29%	8%
Fraser-Cascade	20%	27%	7%
Gold Trail	20%	25%	5%
Vancouver Island North	18%	25%	7%
Coast Mountains	18%	23%	5%
Vancouver Island West	24%	23%	-2%
Campbell River	17%	23%	5%

Source table

The districts with the highest absence rates for designated students are almost entirely remote northern and coastal communities. Nisga’a at 48%, Stikine at 35%, Central Coast at 31%, Prince Rupert at 29%, Fraser-Cascade at 27% — these figures are not marginal variations from the provincial norm. They represent disabled students missing between one quarter and nearly half of all school days.

This data is consistent with what is already documented about these communities: geographic isolation that makes specialist support difficult to deliver, small school sizes that have difficulty retaining dedicated disability support infrastructure, and the ongoing impacts of colonial policy on Indigenous families’ relationships with educational institutions. What the data makes plain is that whatever the province’s reconciliation commitments describe, these outcomes are not consistent with them.

Coast Mountains, Gold Trail, Vancouver Island North, and Campbell River complete this list — mid-sized remote districts where designated student absence runs between 23% and 25%. These are communities where the support that would make attendance possible for disabled students is likely unavailable or intermittent.

Vancouver Island West remains the anomaly at 23% designated absence with a -2% gap. This compressed gap almost certainly reflects small populations and community-wide barriers rather than effective inclusion practice.

What unites every district on this list is not a single cause but a single outcome: disabled children missing enormous amounts of school in communities the province has consistently underserved. The historic investments the Ministry announces do not appear to be reaching these children.

Gap between children with and without designations

There’s also a significant gap between children with and without designations:

District	No designation	Has designation	Difference
Nisga’a	30%	48%	18%
Prince Rupert	21%	29%	8%
Fraser-Cascade	20%	27%	7%
Vancouver Island North	18%	25%	7%
Boundary	14%	20%	7%
Central Coast	25%	31%	6%
Cowichan Valley	16%	22%	6%
Campbell River	17%	23%	5%
Stikine	30%	35%	5%
Okanagan Skaha	13%	18%	5%

Source table

The gap between designated and non-designated absence — the disability-specific failure visible above whatever community baseline already exists — is largest in Nisga’a at 18 percentage points. But the districts with the largest gaps are not all the same in terms of remoteness, and that variation is worth noting.

Nisga’a, Prince Rupert, Fraser-Cascade, Vancouver Island North, and Central Coast are all remote or rural districts with high Indigenous student populations and limited specialist support infrastructure. The gaps here — ranging from 6 to 18 points — sit on top of already elevated non-designated absence rates. Both the community baseline and the disability-specific failure are present simultaneously.

Boundary is the outlier in this list. Non-designated absence at 14% — close to the provincial norm — with a 7-point gap. Boundary serves the communities of Grand Forks and Rock Creek in the southern interior. It is not a remote district, not predominantly Indigenous, not facing the same geographic barriers as the northern and coastal districts. A 7-point gap in that context is harder to explain through resource constraint or community-level factors alone. It sits more squarely in the institutional failure category — a district with no obvious structural excuse for the size of its disability gap.

Cowichan Valley (6 points) and Campbell River (5 points) are mid-sized Vancouver Island districts with significant Indigenous populations and a mix of urban and rural communities. The gaps here are consistent with the pattern of inadequate support infrastructure in districts that are large enough to have some specialist capacity but not enough to serve their designated student populations well.

Okanagan Skaha (5 points) covers Penticton and the surrounding area — a mid-sized Okanagan district where the gap is notable precisely because there is no obvious geographic or demographic explanation for it.

Districts with most absence for student with no designation

The largest absence levels for students without a designation is present in many of the same Districts have high absence rates for their disabled peers: 

District	No designation	Has designation	Difference
Nisga’a	30%	48%	18%
Stikine	30%	35%	5%
Central Coast	25%	31%	6%
Vancouver Island West	24%	23%	-2%
Prince Rupert	21%	29%	8%
Gold Trail	20%	25%	5%
Fraser-Cascade	20%	27%	7%
Quesnel	20%	21%	2%
Nechako Lakes	19%	22%	3%
Haida Gwaii	19%	21%	2%

Source table

The ten districts where non-designated students are absent 19% or more share several features: most are remote or rural, most serve high proportions of Indigenous students, and many lacking specialist infrastructure — behaviour support teams, mental health counsellors, speech language pathologists — that larger urban districts take for granted. In many of them, getting specialist support to a school means waiting for someone to drive or fly in from a regional centre.

But the disability gap tells different stories within this group.

Nisga’a stands apart. A 30% non-designated rate and a 48% designated rate — an 18-point gap, the largest in the province — suggests two distinct failures operating simultaneously: the community-level factors elevating absence for everyone, and a disability-specific institutional failure adding 18 points on top. Prince Rupert (8 points) and Fraser-Cascade (7 points) show the same pattern at a smaller scale — the disability gap is clearly visible above the community baseline, suggesting inadequate support infrastructure rather than community factors alone.

Stikine, Central Coast, Vancouver Island West, and Haida Gwaii tell a different story. High baseline absence, compressed gaps. These are the province’s most isolated communities — some accessible only by air — where community-level factors dominate the picture so completely that the disability-specific failure, while almost certainly present, is harder to distinguish in the data. Vancouver Island West is the only district in the province where designated students attend at a marginally better rate than non-designated peers — almost certainly a function of very small populations rather than exceptional inclusive practice.

Quesnel, Nechako Lakes, and Gold Trail sit between these patterns — moderate gaps in communities where economic stress and inadequate disability infrastructure appear to be contributing simultaneously.

None of these districts represents a success story. A compressed gap on a high baseline is not inclusion. It is uniform failure.

Absence by designation

Every school has a finite amount of institutional attention, accommodation capacity, and goodwill to extend toward students whose needs diverge from the standard offering. Schools have been chronically underfunded and this lack of capacity does not land equally on all children. The question this data answers is: toward which students does that capacity flow?

Designation	Absence Rate
Non Inclusive Education	12%
Gifted	9%
Learning Disability	13%
Mild Intellectual Disability	18%
Moderate to Profound Intellectual Disability	17%
Autism Spectrum Disorder	16%
Intensive Behaviour Intervention/Serious Mental Illness	20%
Moderate Behaviour Support/Mental Illness	16%
Deaf or Hard of Hearing	11%
Deafblind	16%
Physical Disability or Chronic Health Impairment	17%
Physically Dependent	21%
Visual Impairment	12%

Source table

The answer is consistent across school sizes, across districts, and across two school years: capacity flows toward the children whose difference the institution finds legible, interesting, or manageable. Gifted students attend at rates better than students with no designation at all. Their needs, when acknowledged, are met by stretching the curriculum upward. The building does not have to change.

Autistic students, behaviour-designated students, students with mild or moderate intellectual disability — these are children whose needs require the building to change. The result is absence: a province-wide pattern of disabled children missing between one and two days of school per week more than their non-designated peers, with no meaningful improvement between the two years we can measure.

How the designation system sorts children

Here’s a few important notes about how designations work:

• One designation per child for tracking. Students are permitted only a single designation per enrolment period.
• Autistic+Gifted=Autistic. A child who is both autistic and gifted cannot appear in the gifted column, as they would be coded as autistic, as it carries higher funding.
• Gifted = intelligent across many subjects with no disability. The gifted column, by definition, contains only students whose sole identified difference is upward cognitive variance—no diagnosed autism, behaviour designation, or learning disability.
• Behaviour categories absorb other designations. The behavioural designations (H and R, combined here) operate in the opposite direction. Rather than excluding complexity, they absorb it. Very different children—demand-avoidant, traumatised, awaiting autism diagnosis, neurologically complex—are grouped together, and the absence rate becomes an average across fundamentally different experiences, unified primarily by how the system responds to them.
• Learning Disability is legible. Apparent differences between categories partly reflect this sorting process. Learning Disability appears comparatively stable, in part because it captures needs the system has some infrastructure to read as legible and address. But it is also a residual category. Students whose needs escalate or disrupt are often reclassified into behavioural designations. The system is not only measuring need; it is organising children by how difficult their needs are perceived.

Who is missing from the data entirely

Many disabled children do not appear in any designation column at all. A formal inclusive education designation requires a formal diagnosis, which in BC often means a private psychological assessment costing several thousand dollars—a barrier that falls unevenly across families.

In communities with less affluence or remote communities, fewer families can access the diagnostic process, which means more disabled children are enrolled without a designation and appear in the non-designated column instead. This may contribute to elevated non-designated absence rates in lower-income communities, and it means the gap between designated and non-designated students likely understates the true scale of disability-related absence.

A note on scale

Some designation groups are very small. At the school or district level, their absence rates may reflect the experience of one or two students rather than a stable pattern. This analysis therefore focuses on larger populations—Autism, Behavioural/Mental Health, Learning Disability, Intellectual Disability—and treats smaller groups with caution.

What school size reveals — and what it doesn’t

The relationship between school size and the absence gap raises questions that the data alone cannot answer, but that families in this community may recognise.

Designation	Tiny	Small	Medium	Large	Very Large
Non Inclusive Education	16%	16%	14%	14%	12%
Gifted	9%	8%	12%	8%	9%
Learning Disability	13%	19%	13%	13%	13%
Mild Intellectual Disability	24%	18%	14%	16%	18%
Moderate to Profound Intellectual Disability	9%	15%	17%	17%	18%
Autism Spectrum Disorder	23%	18%	14%	17%	16%
Intensive Behaviour Intervention/Serious Mental Illness	17%	29%	18%	17%	21%
Moderate Behaviour Support/Mental Illness	16%	17%	14%	16%	16%
Deaf or Hard of Hearing	8%	10%	15%	12%	11%
Deafblind				5%	17%
Physical Disability or Chronic Health Impairment	17%	16%	18%	18%	17%
Physically Dependent	13%	84%	15%	41%	20%
Visual Impairment	28%	15%	16%	16%	12%

Source table

• Non-designated absence: 16% in tiny schools, 12% in very large ones — falling consistently as schools grow, reflecting the resource advantages of scale.
• Gifted students: 8–12% across all school sizes — tracking close to the non-designated baseline throughout.
• Intensive Behaviour: 29% in small schools, 21% in very large ones — worst in small schools consistent with the resource constraint argument, but remaining elevated in large schools consistent with the process exclusion argument.
• Autism Spectrum: 23% in tiny schools, 14% in medium schools — improving through medium schools then rising again at large and very large schools.
• Physically Dependent: 84% in small schools — almost certainly a data artefact reflecting one or two students with complex medical circumstances rather than a stable pattern. Blank cells indicate populations too small to produce a reliable median for that school size.

School size shapes the absence gap in two distinct ways:

• The first is relational. In large schools, staff turnover, departmental structures, and sheer scale mean that a child’s history — their triggers, their good days, their family context — may not follow them from year to year or classroom to classroom. In small schools, the opposite is true: staff know children across years, know their families, know the history. That intimacy can be protective. It can also calcify into fixed narratives — this child is difficult, this family is demanding — that are harder to dislodge precisely because they feel personal and earned rather than bureaucratic and arbitrary. Where a large school might fail a child through indifference, a small school can fail them through certainty.
• The second is budgetary. A large school with 800 students and a correspondingly large budget has flexibility that a school of 80 students simply does not. Even with identical per-student funding, a large school can employ a behaviour support teacher, a counsellor, multiple EAs, and still have administrative capacity to coordinate between them. A small school covers fixed costs first — principal, secretary, heating — and supports whatever is left with what remains. When a small rural school has two H-coded students having a difficult week, there is one vice-principal and whatever goodwill is left in the room.

Both dynamics produce the same outcome through different paths. Large schools exclude through process — policy, timetabling, support planning frameworks that no single person authored or intended. Small schools exclude through relationship — the accumulated weight of years of knowing, which can tip from empathy into a kind of scapegoating logic where some children come to be seen as the problem rather than as vulnerable children who are rights bearers.

What demographics reveal about the gap

To understand whether the absence gap reflects something specific about disability and institutional response — rather than simply the characteristics of communities and schools — we cross-referenced the absence data with demographic information from the Ministry’s published enrolment data averaged across these years.

We classified schools by four demographic variables: concentration of English Language Learners, concentration of Indigenous students, concentration of students with disabilities or diverse abilities, and concentration of French Immersion enrolment. This choice of classification was based on the limitation of the public data sets accessible at this time. Each variable was classified as Low, Medium, or High based on the distribution across BC schools.

These four variables were chosen because they are available in the Ministry’s publicly accessible enrolment data and because each serves as a proxy for a distinct dimension of school community context:

• ELL concentration as a marker of recent immigration and associated socioeconomic pressures;
• Indigenous concentration as a marker of the communities most directly affected by colonial education policy;
• disabilities concentration as a measure of the school’s overall inclusive education population; and
• French Immersion concentration as a proxy for socioeconomic advantage, given that French Immerson programs are disproportionately accessed by families with more resources and institutional knowledge.

We acknowledge that these are imperfect proxies, and that richer demographic analysis would benefit from additional variables — including income data, geographic remoteness indices, and school-level staffing information — but our bandwidth to source additional data sets is limited.

English language learners

Has designation?	Low	Medium	High
No	14%	11%	11%
Yes	17%	14%	13%

Source table

ELL concentration produces the cleanest pattern. Higher ELL concentration is associated with lower absence for both groups consistently — a socioeconomic suppression effect, where families in high-ELL communities tend to have less flexibility to keep children home or respond to school phone calls. The gap between designated and non-designated students stays remarkably stable at 3 points across all three ELL categories. ELL concentration moves the floor for everyone without changing the system’s differential treatment of disabled students.

Indigenous students

Has designation?	Low	Medium	High
FALSE	10%	14%	21%
TRUE	13%	18%	23%

Source table

Indigenous concentration is the most devastating finding in this analysis. Absence climbs dramatically for both groups as Indigenous concentration increases—non-designated students in high-Indigenous schools are absent 21% of the time, already a crisis by any measure, and designated students 23%.

These figures likely reflect the accumulated impacts of geographic isolation, inadequate specialist support infrastructure, and the ongoing consequences of colonial policy on communities the province has systematically under-resourced.

The disability gap actually compresses in high-Indigenous schools—not because disabled students are better served, but because the floor for everyone is already so low. The compression may also reflect diagnostic inequity: many disabled children in under-resourced communities may remain undesignated, appearing in the non-designated column and pulling its absence rate upward, which narrows the visible gap between the two groups whilst masking the true scale of disability-related absence.

When a school is failing all its students so comprehensively, the concept of differential treatment has been overtaken by uniform failure. Within this pattern, one figure is worth naming specifically: Gifted-designated students in high-Indigenous schools are absent at only 8% — lower than anywhere else in the province, and 17 points below their Intensive Behaviour peers in the same schools.

Disabled Students

Has designation?	Low	Medium	High
FALSE	11%	13%	32%
TRUE	13%	17%	34%

Source table

Disabilities concentration shows the most alarming absolute figures. In high-disability-concentration schools, non-designated students are absent 32% of the time and designated students 34%. Perhaps, the gap is compressed because the whole school is under extraordinary pressure to juggle resources. 

French immersion students

Has designation?	Low	Medium	High
FALSE	12%	17%	11%
TRUE	15%	21%	14%

Source table

French Immersion concentration is the socioeconomic signal — and the most revealing for the disability exclusion argument specifically. Medium French immersion schools show the largest gap: non-designated at 17%, designated at 21%, a 4-point difference.

High-French immersion schools — the most affluent — show lower absence for both groups and a consistent 3-point gap. Whether that reflects better support or better legal caution is a question this data cannot answer. What it confirms is that the gap persists even in the province’s most affluent public schools.

Why the absences?

At first glance, the absence reason data appears to offer explanation. Illness, parent excused absences, appointments — a familiar set of categories that suggest ordinary life interrupting school attendance. Look more closely, and a different picture emerges.

A methodological note before reading: because these are medians rather than shares of a single pie, the figures do not sum to 100%. Each cell represents the middle value across all schools for that reason and designation group. Read the figures directionally rather than as precise proportions.

Designation	Appointment	Illness	Parent Guardian Excuse	Unspecified	Vacation
Non Inclusive Education	2%	22%	15%	47%	5%
Gifted	1%	24%	14%	28%	2%
Learning Disability	1%	19%	14%	51%	2%
Mild Intellectual Disability		13%	10%	62%
Autism Spectrum Disorder	2%	20%	16%	46%	2%
Intensive Behaviour Intervention/Serious Mental Illness	1%	13%	13%	60%
Moderate Behaviour Support/Mental Illness	1%	17%	13%	56%
Deaf or Hard of Hearing	1%	17%	11%	41%
Deafblind		10%	13%	50%
Moderate to Profound Intellectual Disability		11%	10%	57%
Physical Disability or Chronic Health Impairment	2%	17%	14%	50%
Physically Dependent		10%	15%	48%
Visual Impairment		14%	12%	40%

Source table

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• The dominant category across every designation is Unspecified.
• Intensive Behaviour: 60% Unspecified. Moderate Behaviour Support: 56%. The highest among the behavioural designations.
• Mild Intellectual Disability: 62% Unspecified. Moderate to Profound Intellectual Disability: 57%.
• Non-designated students: 47% Unspecified. The system does not know — or has chosen not to record — why the majority of students are not in school, regardless of designation.
• Gifted: 28% Unspecified — nearly 20 points below the non-designated baseline and far below every disability designation.
• Illness: highest for Gifted at 24%, lowest for Intensive Behaviour and Mild Intellectual Disability at 13% — likely due to conscientious reporting for the former and exhaustion for the latter.
• Parent/Guardian Excuse: 10% for Mild Intellectual Disability and Moderate to Profound Intellectual Disability, 16% for ASD. Relatively flat across designations — it measures contact between school and family rather than the underlying cause of absence.
• Vacation: 5% for non-designated students, 2% for Gifted, Learning Disability, and ASD, 0% for every other disability designation. Families navigating the most intensive designations do not take school-day holidays at measurable rates. For many, unplanned absence is already a survival strategy. A planned holiday is not part of the picture.
• All other reason codes — suspension, weather, field trips, cultural activities, school-authorised absences — register at zero across every designation at the median. The exclusion this dataset documents is not happening through the formal mechanisms the system has names for. It is happening through the mechanisms it has chosen not to name.

What the reasons data ultimately confirms is not an explanation for the absence gap but a description of the system’s chosen relationship with that gap. The majority of absences — for every student, of every designation — are recorded without explanation. The system that is failing to keep disabled students in school is also failing, or declining, to document why they are missing school.

What suspension data says

A note before we examine the suspension data: formal suspensions are rare in this dataset. The median school records zero suspensions for every designation, and the overall suspension rates are small enough that averages across schools should be interpreted with caution — a single school with an unusual pattern can move the provincial figure meaningfully.

What the data cannot do is tell us how many suspensions occurred in absolute terms, only what share of recorded absence they represent. We present these figures not as a definitive account of suspension patterns in BC schools but as a directional signal — and the direction is consistent and striking. Whatever the absolute numbers, the suspension burden in this data falls with disproportionate concentration on disabled students, and on the students already carrying the highest absence rates. That pattern is worth naming even in a small and imperfect dataset.

Designation	Percentage of total
Non Inclusive Education	5%
Gifted	3%
Learning Disability	9%
Mild Intellectual Disability	10%
Autism Spectrum Disorder	4%
Intensive Behaviour Intervention/Serious Mental Illness	25%
Moderate Behaviour Support/Mental Illness	18%
Deaf or Hard of Hearing	6%
Deafblind	0%
Moderate to Profound Intellectual Disability	6%
Physical Disability or Chronic Health Impairment	7%
Physically Dependent	0%
Visual Impairment	7%

Source data

• Intensive Behaviour / Serious Mental Illness: 25% of all suspension-coded absence. Moderate Behaviour Support / Mental Illness: 18%. Together, behaviour-designated students account for 43% of all formally recorded suspension absence — from a group representing a small fraction of the total student population.
• Gifted students: 3% of suspension-coded absence — lower than non-designated students at 5%, consistent with every other measure in this dataset.
• Autistic students: 4% of suspension-coded absence, despite substantially elevated overall absence rates. Members of our group have raised the question of whether funding considerations create a disincentive to formally suspending autistic students — a hypothesis the data does not contradict.
• Learning Disability and Mild Intellectual Disability combined: nearly 20% of suspension-coded absence — higher than their population share would predict and worth further investigation.
• For other designation groups, population sizes are too small to draw conclusions. The headline finding is not that suspension is common — the median school records zero formal suspensions for every designation. It is that when formal suspension does occur, it falls with extraordinary concentration on the students already carrying the heaviest absence burden.

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What this means for families

In every single BC school district, disabled students are absent at higher rates than their non-disabled peers.

The gap is smallest in affluent urban schools and largest in remote northern and Indigenous communities, but it is present everywhere.

Autistic students, behaviour-designated students, and students with intellectual disabilities miss between one and two additional days of school per week compared to their non-designated peers—a pattern that holds across two years of data, across school sizes, and across demographic contexts.

The system records the majority of these absences as “Unspecified.” Any competent database administrator keeps “Other” values below 5%. The Ministry has allowed more than half of all absence records to sit in an unusable category for years. This is not a technical limitation. It is an indictment of their professional judgement. If you don’t count it, you can’t see it.

You only ignore data quality this poor, across multiple years, when you’re committed to ensuring the pattern never becomes visible.

Just a Parent

When formal suspension does occur, it falls with extraordinary concentration on behaviour-designated students, who account for 43% of all suspension-coded absence despite representing a small fraction of the student population. The absence rate for gifted students—8% to 12% depending on school context—sits consistently below the non-designated baseline, confirming that the system performs differently for different children within the same buildings, with the same resources, in the same years.

These figures represent hundreds of thousands of school days lost to disabled children across BC. They are the provincial impact of every phone call asking a parent to pick up their child early, every partial schedule framed as a support plan, every quiet arrangement that kept a child home because the support that was supposed to be in place was not there. The data does not tell us why disabled children are missing school at these rates. It tells us that they are, and that the system has chosen not to document this information or explain why vulnerable children’s needs are not being met.

Further analysis is coming!