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Token economies are among the oldest and most successful teaching programs in applied behavior analysis. Despite a rich history of basic and applied research on token systems, there remains a research‐to‐practice gap. Our aim in this paper is to bridge this gap between research and application, by providing evidence‐based recommendations and practical guidelines for application of token reinforcement methods. The recommendations in Part 1 are for building a token economy from the ground up, in learners without a history of token reinforcement, whereas those in Part 2 are concerned with existing token economies without regard to how they were established. Although token economies have proven generally effective across a range of settings and populations, they could be even more effective when based on the latest research and theory. Thus, apart from specific recommendations, we hope to show the benefits of an integrated evidence‐based approach to the application of token reinforcement principles in educational and clinical settings. [ABSTRACT FROM AUTHOR]

Pigeons made repeated choices between earning and exchanging reinforcer-specific tokens (green tokens exchangeable for food, red tokens exchangeable for water) and reinforcer-general tokens (white tokens exchangeable for food or water) in a closed token economy. Food and green food tokens could be earned on one panel; water and red water tokens could be earned on a second panel; white generalized tokens could be earned on either panel. Responses on one key produced tokens according to a fixed-ratio schedule, whereas responses on a second key produced exchange periods, during which all previously earned tokens could be exchanged for the appropriate commodity. Most conditions were conducted in a closed economy, and pigeons distributed their token allocation in ways that permitted food and water consumption. When the price of all tokens was equal and low, most pigeons preferred the generalized tokens. When token-production prices were manipulated, pigeons reduced production of the tokens that increased in price while increasing production of the generalized tokens that remained at a fixed price. The latter is consistent with a substitution effect: Generalized tokens increased and were exchanged for the more expensive reinforcer. When food and water were made freely available outside the session, token production and exchange was sharply reduced but was not eliminated, even in conditions when it no longer produced tokens. The results join with other recent data in showing sustained generalized functions of token reinforcers, and demonstrate the utility of token-economic methods for assessing demand for and substitution among multiple commodities in a laboratory context. [ABSTRACT FROM AUTHOR]