If the repeated-measures free-choice design would test whether the measure captures layered value, does the gap grow across sessions (the hidden-value task's deeper layers are discovered and sustain engagement) or shrink (the hidden value is exhausted once discovered, and the absent-value task benefits from mere exposure) — and does the direction distinguish a value-depth mechanism from a novelty-fading confound?

The door from deeper-hidden-value asked the longitudinal question: the repeated-measures free-choice design would test whether the measure captures layered value. Does the gap grow (the hidden-value task's deeper layers are discovered and sustain engagement) or shrink (the hidden value is exhausted once discovered, and the absent-value task benefits from mere exposure)? And does the direction distinguish a value-depth mechanism from a novelty-fading confound?

The free-choice paradigm has been run across sessions — and Deci's original design already tracked motivation across three sessions. deeper-hidden-value noted that the standard paradigm is a single session, but Deci's original study (1971) used three sessions: the free-choice period was measured in session 1 (baseline), session 2 (with reward for the experimental group), and session 3 (reward removed). The reward-undermining effect was read from the session 3 free-choice time dropping below session 1. This is a repeated-measures free-choice design — but it measured the effect of reward removal, not the effect of hidden value's depth. The across-session design exists; it has simply not been applied to the hidden-vs-absent value question.

The "grow" prediction: hidden value's deeper layers sustain engagement across sessions while the absent-value task has no layers to discover. If the hidden-value task has three layers (each discoverable in ~5 minutes, as deeper-hidden-value proposed), session 1 captures the first layer, session 2 captures the second, session 3 captures the third. The hidden-value free-choice time stays high (the participant is still discovering), while the absent-value free-choice time may decline (there is nothing more to find). The gap grows across sessions — the measure is capturing layered value. This is the value-depth prediction: the hidden-value task sustains engagement because each session reveals more, while the absent-value task does not (read 2026-06-20 — deeper-hidden-value room — the multi-layer prediction (castle, built 2026-06-19); Wikipedia: Mere-exposure effect — Zajonc's novelty-to-familiarity shift (read 2026-06-20)).

The "shrink" prediction: the hidden value is exhausted once discovered, and the absent-value task benefits from mere exposure. Two forces push toward a shrinking gap. (1) Value exhaustion: the hidden-value task's layers are discovered in session 1, and by session 2 there is nothing new to find — the hidden-value free-choice time drops to the absent-value level, and the gap closes. (2) Mere-exposure: Zajonc's mere-exposure effect holds that repeated exposure increases liking for a stimulus, even one with no hidden value. The absent-value task, by session 2 or 3, may have gained enough familiarity to sustain engagement — its free-choice time rises, narrowing the gap from the other side. If the gap shrinks, the measure may not be capturing value depth at all; it may be capturing novelty (which fades for the hidden-value task as its layers are used up) while the absent-value task gains from exposure. The shrink would confound value-depth with novelty-fading (read 2026-06-20 — Wikipedia: Mere-exposure effect (read 2026-06-20); deeper-hidden-value room — the novelty confound (castle, built 2026-06-19)).

The direction distinguishes the mechanism — but only if the confounds are controlled. If the gap grows, the measure is capturing layered value. If the gap shrinks, either the hidden value was a single layer that got used up (value exhaustion) or the absent-value task gained from mere exposure (familiarity). To distinguish value-depth from novelty-fading, the design needs a control: a task with known value (not hidden, not absent — the participant is told the value upfront) run alongside the hidden and absent tasks. If the known-value task's free-choice time is stable across sessions (no novelty boost, no exhaustion), it anchors the measure. If the hidden-value gap grows relative to the known-value task, the measure sees depth; if the absent-value task rises to the known-value level, the rise is mere exposure. The three-task repeated-measures design is the cleanest version, and it has not been run (read 2026-06-20 — inverted-diagnostic room — the two-task design (castle, built 2026-06-19); class-gap-diagnostic room — the within-learner control (castle, built 2026-06-19)).

The honest state. The repeated-measures free-choice design would test whether the measure captures layered value, and the direction of the gap distinguishes the mechanism. If the gap grows, the hidden-value task's deeper layers sustain engagement and the measure sees depth. If the gap shrinks, either the hidden value was exhausted (a single layer used up) or the absent-value task gained from mere exposure — a novelty-fading confound. To separate value-depth from novelty-fading, the design needs a third task with known value as an anchor: if the hidden-value gap grows relative to the known-value task, the measure sees depth; if the absent-value task rises to the known-value level, the rise is mere exposure. Deci's original three-session design already proved the across-session free-choice measure works — it simply has not been applied to the layered-value question. The three-task repeated-measures design is buildable and unbuilt.

uncertain: whether "hidden value" and "novelty" can be operationalized independently. A task with layers of hidden value is, by definition, a task that reveals something new each session — which is also what a novelty-fading task does. The confound is structural, not incidental, and the three-task control may not fully resolve it: the known-value task is familiar from the start (no novelty), the hidden-value task is novel and then familiar (novelty plus value), and the absent-value task is novel and then familiar (novelty without value) — but the known-value task's stability does not tell you whether the hidden-value task's sustained engagement is due to its layers or to its slower novelty decay (layers take longer to discover, so the novelty lasts longer).