Construct · 3 fields · 3 citations

Where does lift collide?

One name. Different field. Different construct. One map.

● jingle · one word, three constructs Nearest construct by meaningsupportcompare the meanings
How to read this

Every construct on the map is compared with every other by the meaning of its definitions, and the closest one is surfaced here. The nearest construct to lift is support.

Hold this as a prompt, not a verdict. Two constructs sitting close in meaning is a reason to read them side by side and decide for yourself whether they are one idea under two names. It is not proof that they are. Compare the meanings in the Collider.

lift3 CONSTRUCTSAerodynamic liftBABINSKY · AERO FORCEAssociation liftBRIN · CO-OCCUR RATIOSales liftLO · SALES INCREMENT

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2026

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Fluid dynamics and aerodynamics

Force perpendicular to the flow that supports a wing

The component of the aerodynamic force on a body moving through a fluid that acts perpendicular to the oncoming flow, and on an aircraft it is the upward force that supports the weight: as air is turned and accelerated around a wing, a pressure difference builds between the two surfaces and the net force across the flow is the lift. Babinsky's 2003 article How do wings work? in Physics Education explains this pressure difference and the circulation of air around the aerofoil, the basis of the dimensionless lift coefficient and of the Kutta-Joukowski theorem that ties lift to that circulation. The referent is a physical force measured on a moving body, not a statistical ratio comparing observed with expected co-occurrence, and not the extra sales caused by an advertising campaign.[1]

Unit
An upward force on a body in a fluid, in newtons, or as a dimensionless lift coefficient
Recovery means
Not applicable
Measured by
Found in a wind tunnel from a force balance, or computed from the pressure distribution and the circulation around the surface

Data mining and association rules

Ratio of observed to expected co-occurrence

In data mining, a number attached to an association rule that says how much more often two items appear together than they would if they were unrelated: it is the rate at which the items are observed together divided by the rate expected if each occurred independently, so a value above one marks a positive association and a value of one marks none. Brin, Motwani, Ullman, and Tsur's 1997 paper Dynamic itemset counting and implication rules for market basket data introduced this ratio, which they called interest, to rank rules in the market-basket analysis of what shoppers buy together. The referent is a dimensionless descriptive ratio computed from counts, not an upward force on a wing, and not the increase in sales that a campaign actually causes.[2]

Unit
A ratio of observed to expected co-occurrence, dimensionless, centred on one
Recovery means
Not applicable
Measured by
Computed from transaction counts as the confidence of a rule divided by the overall frequency of its consequent item

Marketing and causal inference

Increase in an outcome caused by a treatment

In marketing and causal inference, the increase in an outcome such as sales, conversions, or responses that is caused by a treatment such as an advertising campaign or a promotion, measured as the difference between what happened with the treatment and what would have happened without it. Lo's 2002 article The true lift model in the ACM SIGKDD Explorations Newsletter set out how to estimate this incremental effect for individual customers and target those whose behaviour the treatment actually changes, an approach now called uplift modelling. The referent is a causal increment estimated by comparing treated with untreated groups, not a physical force on a wing, and not a descriptive ratio of how often two items are bought together.[3]

Unit
The extra outcome caused by a treatment, as a difference in rates or counts
Recovery means
Not applicable
Measured by
Estimated from a randomised test-and-control comparison, as the treated response rate minus the control response rate

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Nearby collisions

drag3 fields · 4 citationsjingle · one word, three constructsbasket2 fields · 3 citationsjingle · one word, two constructscirculation4 fields · 4 citationsjingle · one word, four constructs

References

  1. Babinsky, H. (2003). How do wings work? Physics Education, 38(6), 497–503. https://doi.org/10.1088/0031-9120/38/6/001
  2. Brin, S., Motwani, R., Ullman, J. D., & Tsur, S. (1997). Dynamic itemset counting and implication rules for market basket data. In Proceedings of the 1997 ACM SIGMOD International Conference on Management of Data (pp. 255–264). https://doi.org/10.1145/253260.253325
  3. Lo, V. S. Y. (2002). The true lift model: A novel data mining approach to response modeling in database marketing. ACM SIGKDD Explorations Newsletter, 4(2), 78–86. https://doi.org/10.1145/772862.772872

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