Variability of responding on a concurrent schedule as a function of body weight.

Researchers worked with pigeons on two variable-interval food schedules at once. They slowly raised each bird's body weight from 80% to 110% of free-feeding weight. The team then counted how steady or jumpy the birds' key pecks became.

As the birds got heavier, their peck rates swung more wildly. The spread of responses grew, even though the overall number of pecks stayed about the same. In short, heavier birds showed more variable timing, not more pecks.

Lalli et al. (1995) later showed that food density, not just clock time, sets the shape of VI response curves. Their work builds on Rodewald (1974) by proving the key factor is how much food is available per minute, not body weight alone.

Myerson et al. (2007) found a matching rule in people: once you account for speed, older adults are no more variable than younger ones. Both papers warn us to look at the mean first before we call a response pattern 'unstable.'

Iwata et al. (1990) reviewed human weight-loss programs and noted that staying consistent with skills keeps weight off. The pigeon data remind us that even small weight changes can ripple through behavior, so we should track weight in any study that uses food reinforcers.

If you run food-based reinforcement sessions, weigh your client or animal first. A small weight shift can make response rates look messy and mask real learning. Record the mean and the spread; both can tell different stories. Use this insight when you design schedules or interpret data that feel 'noisy.'