Frequently Asked Questions

KLaSAn (Kifuliiru Language Simulator and Analyzer) is a public platform for measuring, analyzing, simulating, and preserving Kifuliiru. It is also known as Kifuliiru Observatory (KObs), Kifuliiru Radar, and LaSAn in public-facing copy — these are aliases for the same application, not separate products.

LaSAn (Language Simulator and Analyser) is a numerical framework by Wekify LLC that defines 68 language resource units across eight categories. KLaSAn uses LaSAn to score Kifuliiru documentation progress, compute the Language Resource Index (LRI), drive status labels, and power the simulation and radar views.

KLaSAn is built for Kifuliiru — also known as Fuliiru or Fuliru (ISO 639-3: flr). Metrics, corpus mappings, and simulations are calibrated for Kifuliiru documentation and vitality, though the LaSAn framework itself is language-agnostic.

KLaSAn is developed by Wekify LLC in partnership with Kifuliiru Lab. Baseline corpus data comes from Kifuliiru contributors and the Tabula contributor platform. Methodology documents follow the LaSAn Numerical Reference v1.0 (March 2026).

KLaSAn is an observatory and simulator — it aggregates metrics, scores resource health, and models scenarios. The main Kifuliiru website (kifuliiru.com) hosts live data and learner tools; Kifuliiru Lab (kifuliiru.org) publishes research and formulas. Tabula Kifuliiru, Lola Kifuliiru, and the full tool list are on the Discover Tools page (/discover). KLaSAn links to those sites but does not replace them.

The Language Resource Index (LRI) is the average score of all 68 LaSAn resource units, each on a 0–100 scale. LRI = (sum of all 68 unit scores) ÷ 68. It is the primary metric for overall Kifuliiru language resource health in KLaSAn.

LaSAn maps each unit score to status bands. Functional means a score of 46–70 — the resource is usable for real work. Comprehensive means 71–100 — the resource meets the reference ceiling for well-resourced minority languages. Below 46, resources are Partial or Initiated.

LaSAn uses three scale types: Scale A (logarithmic) for count-based resources like dictionary entries; Scale B (linear) for coverage and performance percentages; and Scale C (milestone) for discrete states such as ISO 639 code registration.

Resource Coverage Rate (RCR) measures what share of the 68 units have reached Functional level or above (score ≥ 46). RCR = (count of units with score ≥ 46) ÷ 68 × 100%. It shows breadth of documentation across resource types, not just depth in a few areas.

Critical Gap Count (CGC) counts units with score below 46 that are hard dependencies for other units — for example, missing orthography standards that block spell checkers or textbooks. CGC highlights blockers that prevent downstream resource development.

Ceilings are calibrated against well-resourced minority languages such as Welsh, Basque, Māori, Faroese, and Luxembourgish — languages that achieved functional infrastructure through sustained effort. The ceiling represents an honest aspiration, not a comfortable comparison to majority languages.

LaSAn defines 68 resource units organised into eight categories: Lexical, Grammatical, Text Corpora, Audio and Visual, Educational, Digital and NLP, Standardisation, and Cultural and Ethnographic resources.

Six units are mapped from corpus data today: LEX-01 (general dictionary / words), LEX-02 (bilingual pairs), AUD-01 (audio recordings), GRM-07 (interlinear glossed sentences), COR-01 (general corpus tokens), and LEX-04 (numbers and math vocabulary). The remaining 62 units show placeholder scores until additional data is available.

Baseline counts — words, audio clips, verified entries, sentences, translations, numbers, and related metrics — are sourced from the Kifuliiru contributor corpus and dashboard. When available, live metrics are fetched via the LaSAn API.

A score of 0 means no measurable data is mapped to that unit yet — not that the resource does not exist in the community. As new data types are catalogued (textbooks, radio hours, orthography standards, etc.), units are connected and scores update automatically.

Corpus-linked units refresh as contributors add and verify entries on Tabula. Dashboard and analytics views reflect the latest available snapshot. Major methodology or ceiling changes are documented in release notes on the Methodology page.

The Kifuliiru Radar is the impact visualization in the Simulation section. It plots progress, weighted impact, and scarcity across dozens of levers — corpus entries, publications, adoption metrics, media output, and digital infrastructure — so you can see which inputs move overall language health most.

The simulator covers speakers and adoption, documentation corpus growth, publication and media output, digital and NLP readiness, risk factors (including transmission and stability), milestones, and forecast scenarios. Each area has its own page under /simulation with charts and adjustable variables.

These are effort presets in growth projections. They map to different assumptions about active contributors, words per month, audio per month, and related rates. Use them to compare conservative vs ambitious documentation trajectories without editing every variable manually.

Transmission Break Point (TBP) is a critical threshold in the Risks model — typically around 0.5 — above which intergenerational language transmission is considered at serious risk. It appears in the Simulation → Risks section alongside home transmission, youth fluency, and related levers.

Yes. On Impact → Radar, drag levers on the radar chart or use the variables panel on the right. Counts feed back into impact scores immediately. Category filters on the radar and sidebar stay in sync so you can focus on Adoption, Web & digital, Corpus, or other groups.

Join the contributor community on Tabula (tabula.kifuliiru.com). Adding words, audio, sentences, and verified entries directly improves mapped LaSAn unit scores and flows through to LRI, analytics, and simulation baselines.

Community (/insights) shows who is building the corpus — leaderboard, live activity, contribution heatmap, and contributor growth. Corpus Analytics (/analytics) explains how we interpret the data — completeness, growth, health, and NLP readiness — without a live dashboard on this public site; use the Observatory for live numbers. Simulation lets you adjust levers, run what-if scenarios, and explore risks and forecasts. All three draw from the same underlying LaSAn framework.

Yes. KLaSAn is a public observatory. You can explore dashboards, methodology, resource units, and simulations without an account. Contributing corpus data requires a Tabula contributor account.

Yes. Cite the platform as KLaSAn (Kifuliiru Language Simulator and Analyzer), Wekify LLC & Kifuliiru Lab, with the page URL and access date. For methodology details, reference the LaSAn Numerical Reference v1.0 and the Methodology page.

The Methodology page documents LaSAn scales, LRI, RCR, CGC, status bands, risk formulas, and data sources in full. The Resource Units page lists all 68 units with ceilings and thresholds. This FAQ summarizes common questions — see those pages for technical depth.