Probability and radical behaviorism.

Davison (1992) asked a simple question. What do we mean when we say a rat's bar press has a a large share chance of payoff?

The paper builds a math tool. It treats each peck or press as a coin flip. Heads equals reinforcement. Tails equals extinction.

The author shows how to read a cumulative record like a running scoreboard of these coin flips.

Probability is just the count of reinforcers divided by total responses. Nothing lives inside the bird or rat.

The same math works for both reinforcement and extinction. You only change the coin's bias.

This gives BCBAs a ruler. You can now say, 'Today the coin landed on reinforcement a large share of the time.'

Coe et al. (1997) tested the idea with real pigeons. The birds picked the least common stimulus above chance. Their data fit the coin-flip model.

Jarmolowicz et al. (2021) push the same theme forward. They ask for applied quantitative analysis of behavior, echoing M's call for numbers in daily practice.

Crossman et al. (1985) add a twist. They say generalization is quantal, not smooth. M's coin-flip view is also quantal, each response is a discrete hit or miss.

Stop guessing about motivation. Start counting. Track every response and its consequence for one session. Turn the totals into a simple percentage. Share that number with your team and parents. It gives a clear, math-based picture of how the contingency is working right now.