The behavioral science glossary

Plain-language definitions for the instruments, models, and terms behind Mappa's behavioral assessment for hiring.

See your own behavior map.

A behavioral assessment scored on published, peer-reviewed instruments. Thirty seconds of speech is all it needs — you get the full report, not a teaser.

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Jammil Handal
Client
Mappa's process is smart, efficient, and consistently delivers the right fit for Priority's specific needs.
Jammil Handal, Executive Vice President · MXBuild Priority

Foundational concepts

Psychometrics

Hiring outcomes

Company culture

Assessment instruments

Speech & model terms

  • ParametersSpeech & model terms

    Parameters are the internal values a machine learning model adjusts during training to get better at its task, and what's actually "learned" when people say a model was trained on data.

    What training actually adjusts

    A model doesn't start out knowing anything. It starts with parameters set to something close to random, and training is the process of adjusting those parameters, repeatedly, based on how far off its predictions are, until they settle into values that produce accurate results. Once training is done, the parameters are fixed, and applying the model to something new, called inference, uses those same fixed values without changing them further.

    How it shows up

    A model with more parameters generally has more room to represent complex patterns, but more parameters isn't automatically better. What matters more is whether the parameters were learned from enough of the right kind of data to generalize past it.

    Why it matters at Mappa

    Our voice model's parameters are fixed once training on paired data is complete. Every new recording is scored with that same fixed set of parameters, which is why comparing results across different model versions isn't valid; the underlying parameters aren't the same.

    See what a fixed, validated model reports about you.

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