Every educational, cognitive, psychological, focus, memory, accessibility, and AI claim Glosa makes is graded, sourced, dated, and open to revision. This page is that register in plain view. A source is not a permission slip for overstatement.
A claim in Glosa marketing, onboarding, in-product copy, App Store listing, press release, or investor deck may never exceed the state assigned to it here. States describe what the evidence supports for Glosa's implementation, not what a claim could theoretically achieve in some other product.
Convergent evidence and mature standards support using the principle as a design requirement. Does not mean every implementation produces the effect.
Credible evidence supports the mechanism or outcome — with task, population, and implementation limits.
Direction or magnitude varies meaningfully with material, reader, timing, modality, or design.
Plausible enough to test, but not appropriate as an efficacy or superiority claim.
Evidence is insufficient, the concept is misleading, or the claim would exceed what Glosa can establish.
A source is not a permission slip for overstatement.
Before any claim reaches the public, a review page is filed for it. The review captures:
Marketing may never translate:
If a claim cannot answer the review questions, the copy uses descriptive product language, not efficacy language.
Each row lists what a marketing team might want Glosa to claim, the state assigned to that claim under this register, and the approved language Glosa may use in its place. If a claim you expect is not on this page, it has not been reviewed — and therefore has not been approved.
Preferences configure the interface. Glosa does not diagnose a visual, auditory, or kinesthetic type. The idea failed the science.
A small paper advantage appears in some settings — especially expository reading and self-calibration. Not a general rule; narrative differences are small.
Higher-level comprehension can be similar in some contexts. Modality differences depend on task, material, and population.
Cognitive load, learner, and material matter. No universal advantage established.
Testing and free recall can outperform restudy for delayed retention in many contexts.
Distributed practice is broadly supported. Effective interval depends on retention horizon and material.
Prompts can help; benefits and time costs vary.
Speed–accuracy tradeoff. Very large gains usually sacrifice comprehension or change the task.
Speed is useful for access. Deeper learning depends on material and comprehension.
Effects vary. Intelligible speech or lyrics often interfere. Self-selected sound may help some readers.
ASMR can affect responders' affect and physiology. Comprehension evidence is insufficient.
Product-category claims exceed current Glosa evidence review.
Strong practical and access value. Comprehension benefit depends on reader and material.
Typography preferences and accessibility matter. Universal treatment claims are inappropriate.
Summary supports orientation but removes sequence, evidence, voice, and detail.
AI can offer attributed interpretations. Meaning remains contested and reader-authored.
No validated method. High risk of cultural or spiritual overreach.
Cognitive offloading and ownership research motivate the design. Glosa-specific effect requires testing.
Provenance improves auditability, but sources can be wrong, incomplete, or misrepresented.
Locality reduces transmission but device, storage, and security risks remain.
Goal, material, and prior-knowledge adaptation may help. Opaque profiling and style matching are not justified.
Attention fragmentation can impair encoding. Glosa-specific effect needs testing.
Calibration matters. Paper advantage suggests interfaces should not inflate confidence.
Representations can help when matched to content — not to a fixed visual type.
They are rights-accessible, culturally important, and suitable for product testing. Superiority is not established.
Session length may rise or fall. Longer is not inherently better.
Individual mechanisms have support. Integrated product effect requires trials.
Calm design may be preferred. Mental-health treatment claims require clinical evidence and regulatory review.
AI can retrieve and compare attributed testimony. It has no first-person experience.
Product evaluation can use synthetic fixtures, opt-in studies, and reviewed examples.
Glosa has multiple modes: Savor and Story for immersive reading, Inspectional for orientation, Analytical for study, Listen and Dual for audio, and Research for source-linked comparison. Each mode is allowed a different vocabulary.
Any external Glosa copy — website, App Store listing, onboarding step, paywall, press release, investor deck, or in-product tip — draws only from the approved list. The prohibited list is the specific language a claims review must clear before it can be used at all.
Rev3 outlines seven proposed studies to answer the questions the register leaves open. All are advisory. None has been authorized. Each would use synthetic or public-domain fixtures before private content, distinguish exploratory from confirmatory work, and report null and negative findings alongside positive.
Compare standard scroll, distraction-free scroll, and stable paginated or landmarked reading. Measure comprehension, delayed recall, source-location memory, orientation, and preference.
Compare no AI, answer-first AI, reader-first explanation, and Socratic inquiry. Measure recall, calibration, authorship, assistance dependency, and performance after AI is removed.
Compare silence, self-selected low-information sound, familiar instrumental audio, and ASMR among self-identified responders. Report subgroup effects and harms; do not average away opposite responses.
Compare source only, conventional summary, and source-linked inspectional map. Measure whether readers enter the original, source memory, structural understanding, and false confidence.
Compare text, audio, and dual by material type and task. Include regression and backtracking behavior and delayed outcomes.
Compare editable contextual calibration with quiet default against an opaque “personalized plan.” Measure trust, fit, understanding of adaptation, and data expectations.
Test whether statement typing and source spans improve error detection without overloading the reading experience.
Every proposed public claim — a headline, a feature card, an App Store bullet, a tweet — must answer these nine questions in writing before it can be approved.
If these questions cannot be answered, use descriptive product language rather than efficacy language.
Copy that survives this workflow appears on Glosa surfaces with a claim state next to it and a revision date. Copy that does not survive it does not appear at all.
Glosa is built around evidence-supported reading and learning practices while publishing the limits of every claim. It does not diagnose learning styles, promise impossible speed gains, or replace the work with a summary.
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