diff --git a/agent-radar.json b/agent-radar.json index 3c929d5..83178b3 100644 --- a/agent-radar.json +++ b/agent-radar.json @@ -52,6 +52,22 @@ "tasks_file": "problem-packs/public-health/birth-registration-access-global/tasks.json", "why_pick_now": "Completing this scoped task opens 5 follow-on tasks across 4 additional roles." }, + { + "pack_id": "public-health/oral-health-access-global", + "pack_title": "Oral Health Service Access And Dental Workforce Gaps In Low-Income Countries", + "task_id": "source-inventory", + "title": "Inventory data sources for public-health/oral-health-access-global", + "owner_role": "literature-scout", + "reviewer_needed": "domain-reviewer", + "safety_risk": "low", + "done_condition": "At least four sources classified as usable, limited, or rejected with explicit reasons.", + "evidence_count": 5, + "downstream_tasks_unlocked": 4, + "downstream_high_risk_tasks": 2, + "problem_file": "problem-packs/public-health/oral-health-access-global/problem.md", + "tasks_file": "problem-packs/public-health/oral-health-access-global/tasks.json", + "why_pick_now": "Completing this scoped task opens 4 follow-on tasks across 4 additional roles." + }, { "pack_id": "education/digital-divide-school-access-global", "pack_title": "Digital Divide Measurement And School Internet Connectivity In Low-Income Countries", @@ -100,22 +116,6 @@ "tasks_file": "problem-packs/public-health/ncd-risk-factor-surveillance-global/tasks.json", "why_pick_now": "Completing this scoped task opens 4 follow-on tasks across 4 additional roles." }, - { - "pack_id": "public-health/oral-health-access-global", - "pack_title": "Oral Health Service Access And Dental Workforce Gaps In Low-Income Countries", - "task_id": "source-inventory", - "title": "Inventory data sources for public-health/oral-health-access-global", - "owner_role": "literature-scout", - "reviewer_needed": "domain-reviewer", - "safety_risk": "low", - "done_condition": "At least four sources classified as usable, limited, or rejected with explicit reasons.", - "evidence_count": 1, - "downstream_tasks_unlocked": 4, - "downstream_high_risk_tasks": 2, - "problem_file": "problem-packs/public-health/oral-health-access-global/problem.md", - "tasks_file": "problem-packs/public-health/oral-health-access-global/tasks.json", - "why_pick_now": "Completing this scoped task opens 4 follow-on tasks across 4 additional roles." - }, { "pack_id": "climate-health/malaria-early-warning-africa", "pack_title": "Malaria Early Warning Signals In Sub-Saharan Africa", diff --git a/docs/wiki/Agent-Radar.md b/docs/wiki/Agent-Radar.md index 521b73f..6517f9c 100644 --- a/docs/wiki/Agent-Radar.md +++ b/docs/wiki/Agent-Radar.md @@ -37,7 +37,19 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 5 follow-on tasks across 4 additional roles. - Done condition: At least six candidate sources are classified as usable, limited, or rejected with explicit reasons covering measure family, timing, geographic grain, and health-linkage relevance. -### 2. Digital Divide Measurement And School Internet Connectivity In Low-Income Countries +### 2. Oral Health Service Access And Dental Workforce Gaps In Low-Income Countries + +- Pack: [`public-health/oral-health-access-global`](../../problem-packs/public-health/oral-health-access-global/problem.md) +- Task: `source-inventory` — Inventory data sources for public-health/oral-health-access-global +- Risk: `low` +- Reviewer needed: `domain-reviewer` +- Existing evidence records: 5 +- Downstream tasks unlocked: 4 +- Downstream high-risk tasks: 2 +- Why pick now: Completing this scoped task opens 4 follow-on tasks across 4 additional roles. +- Done condition: At least four sources classified as usable, limited, or rejected with explicit reasons. + +### 3. Digital Divide Measurement And School Internet Connectivity In Low-Income Countries - Pack: [`education/digital-divide-school-access-global`](../../problem-packs/education/digital-divide-school-access-global/problem.md) - Task: `source-inventory` — Inventory school connectivity, mobile-network, and digital-learning data sources for low-income countries @@ -49,7 +61,7 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 4 follow-on tasks across 4 additional roles. - Done condition: At least five candidate data sources are classified as usable, limited, or rejected with explicit reasons covering connectivity-classification methodology, data currency, and cross-validation status. -### 3. Youth Skills Training And Employment Outcome Gaps In Low-Income Countries +### 4. Youth Skills Training And Employment Outcome Gaps In Low-Income Countries - Pack: [`education/skills-training-youth-employment-global`](../../problem-packs/education/skills-training-youth-employment-global/problem.md) - Task: `source-inventory` — Inventory training-provider, employment-outcome, labor-market, and skills-mismatch data sources for LMICs @@ -61,7 +73,7 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 4 follow-on tasks across 4 additional roles. - Done condition: At least five candidate data sources are classified as usable, limited, or rejected with explicit reasons covering provider-data fragmentation, outcome-tracking rates, and informal-sector measurement gaps. -### 4. Non-Communicable Disease Risk Factor Surveillance Gaps In Low-Income Countries +### 5. Non-Communicable Disease Risk Factor Surveillance Gaps In Low-Income Countries - Pack: [`public-health/ncd-risk-factor-surveillance-global`](../../problem-packs/public-health/ncd-risk-factor-surveillance-global/problem.md) - Task: `source-inventory` — Inventory data sources for public-health/ncd-risk-factor-surveillance-global @@ -73,18 +85,6 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 4 follow-on tasks across 4 additional roles. - Done condition: At least four sources classified as usable, limited, or rejected with explicit reasons. -### 5. Oral Health Service Access And Dental Workforce Gaps In Low-Income Countries - -- Pack: [`public-health/oral-health-access-global`](../../problem-packs/public-health/oral-health-access-global/problem.md) -- Task: `source-inventory` — Inventory data sources for public-health/oral-health-access-global -- Risk: `low` -- Reviewer needed: `domain-reviewer` -- Existing evidence records: 1 -- Downstream tasks unlocked: 4 -- Downstream high-risk tasks: 2 -- Why pick now: Completing this scoped task opens 4 follow-on tasks across 4 additional roles. -- Done condition: At least four sources classified as usable, limited, or rejected with explicit reasons. - ### 6. Malaria Early Warning Signals In Sub-Saharan Africa - Pack: [`climate-health/malaria-early-warning-africa`](../../problem-packs/climate-health/malaria-early-warning-africa/problem.md) diff --git a/problem-packs/disaster-resilience/tsunami-early-warning-indian-ocean/evidence.json b/problem-packs/disaster-resilience/tsunami-early-warning-indian-ocean/evidence.json index ceede21..ef069bf 100644 --- a/problem-packs/disaster-resilience/tsunami-early-warning-indian-ocean/evidence.json +++ b/problem-packs/disaster-resilience/tsunami-early-warning-indian-ocean/evidence.json @@ -2,19 +2,20 @@ { "id": "ioc-tsunami-warning-2024", "problem_id": "disaster-resilience/tsunami-early-warning-indian-ocean", - "claim": "UNESCO IOC's Indian Ocean Tsunami Warning and Mitigation System (IOTWMS) has established warning-centre coverage across all Indian Ocean member states, but documented last-mile dissemination gaps and variable community preparedness remain significant operational challenges across the region.", + "claim": "UNESCO IOC coordinates the Indian Ocean Tsunami Warning and Mitigation System (IOTWMS) with warning-centre coverage across Indian Ocean member states, but documented last-mile dissemination gaps and variable community preparedness remain operational challenges.", "evidence_type": "primary-source", "source": { - "title": "UNESCO IOC Tsunami Programme", - "url": "https://www.ioc.unesco.org/en/tsunami-programme" + "title": "UNESCO IOC — Intergovernmental Oceanographic Commission", + "url": "https://www.ioc.unesco.org/" }, "source_date": "2024-01-01", - "access_date": "2026-06-18", + "access_date": "2026-06-28", "method": "Reviewed IOC tsunami programme documentation on IOTWMS warning-system coverage, last-mile dissemination challenges, and preparedness indicators for Indian Ocean member states.", "limitations": [ "Warning-system coverage does not guarantee effective community response — the gap between infrastructure existence and evacuation readiness is not quantified at district level in the public programme pages.", "The specific 'over 60 percent of coastal districts' figure used in earlier versions of this record could not be verified from the IOC programme documentation; the claim has been softened to reflect what the source actually supports.", - "Preparedness indicators are largely self-reported by member states." + "Preparedness indicators are largely self-reported by member states.", + "URL changed from the IOC tsunami programme subpage (404 as of 2026-06-28) to the IOC homepage; the tsunami programme content may have been reorganized." ], "confidence": "medium" } diff --git a/problem-packs/education/digital-divide-school-access-global/evidence.json b/problem-packs/education/digital-divide-school-access-global/evidence.json index 15438aa..1d08abb 100644 --- a/problem-packs/education/digital-divide-school-access-global/evidence.json +++ b/problem-packs/education/digital-divide-school-access-global/evidence.json @@ -65,17 +65,18 @@ "claim": "School census data in many low-income countries includes ICT indicators — computer availability, internet connectivity, electricity — but data currency varies widely (some countries use census data from 5+ years ago) and is not systematically cross-validated against connectivity measurements.", "evidence_type": "expert-review", "source": { - "title": "School census ICT indicators: data quality assessment for low-income countries", - "url": "https://www.unesco.org/en/emis" + "title": "UNESCO Education Sector", + "url": "https://www.unesco.org/en/education" }, "source_date": "2023-06-01", - "access_date": "2026-06-07", + "access_date": "2026-06-28", "method": "Reviewed school census documentation, ICT-indicator availability, data-currency assessment, and cross-validation methodology across low-income countries.", "limitations": [ "Data currency varies enormously — some countries have annual school census updates while others use data from 5+ years ago.", "ICT indicators are self-reported by school administrators — verification against actual connectivity measurements is rare.", "Connectivity definitions used in school censuses vary across countries — 'internet access' may mean different things (any access ever vs. regular usable connection).", - "Cross-validation between Giga satellite data and school census data has been attempted in only a few countries." + "Cross-validation between Giga satellite data and school census data has been attempted in only a few countries.", + "URL changed from the UNESCO EMIS page (404 as of 2026-06-28) to the UNESCO Education Sector page; EMIS content may have been reorganized." ], "confidence": "high" } diff --git a/problem-packs/education/teacher-quality-distribution-global/evidence.json b/problem-packs/education/teacher-quality-distribution-global/evidence.json index 9842ffb..ef921cb 100644 --- a/problem-packs/education/teacher-quality-distribution-global/evidence.json +++ b/problem-packs/education/teacher-quality-distribution-global/evidence.json @@ -65,17 +65,18 @@ "claim": "National EMIS data provides school-level teacher counts and qualification data for some countries, but data quality, update frequency, and public accessibility vary enormously — many countries do not publish sub-national teacher-distribution data, making cross-country deployment-equity comparison methodologically challenging.", "evidence_type": "expert-review", "source": { - "title": "Education Management Information Systems: data quality assessment for low-income countries", - "url": "https://www.unesco.org/en/emis" + "title": "UNESCO Education Sector", + "url": "https://www.unesco.org/en/education" }, "source_date": "2023-06-01", - "access_date": "2026-06-07", + "access_date": "2026-06-28", "method": "Reviewed EMIS documentation, data-quality assessments, and public-availability status across low-income countries.", "limitations": [ "EMIS data quality is self-assessed by national authorities — independent verification is limited.", "Update frequency varies from annual to irregular — some countries use EMIS data that is several years old.", "Public accessibility varies — some countries publish detailed school-level data while others restrict access.", - "Teacher-qualification categories differ across countries — cross-country comparison requires explicit harmonization." + "Teacher-qualification categories differ across countries — cross-country comparison requires explicit harmonization.", + "URL changed from the UNESCO EMIS page (404 as of 2026-06-28) to the UNESCO Education Sector page; EMIS content may have been reorganized." ], "confidence": "high" } diff --git a/problem-packs/public-health/oral-health-access-global/claims.json b/problem-packs/public-health/oral-health-access-global/claims.json new file mode 100644 index 0000000..9c514fd --- /dev/null +++ b/problem-packs/public-health/oral-health-access-global/claims.json @@ -0,0 +1,33 @@ +[ + { + "id": "oral-health-data-scarcity-lmics", + "problem_id": "public-health/oral-health-access-global", + "claim": "Available oral health data sources are sufficient for country-level framing of disease burden and workforce density in low-income countries, but no source provides sub-national oral health service access or dentist distribution data for any low-income country. Sub-national gap mapping is not currently feasible with public data.", + "domain": ["public-health"], + "status": "dry-lab-verified", + "evidence": [ + "who-oral-health-2022", + "who-global-health-observatory-dental-workforce", + "who-oral-health-survey-methods-2013", + "world-bank-health-nutrition-population-stats" + ], + "failure_modes": [ + "A reader treats country-level dentist density as a proxy for sub-national access, masking urban-rural disparities within countries.", + "A reader assumes the absence of sub-national data means access is uniform, rather than that access variation is unmeasured.", + "Ministry-reported workforce counts exclude private and informal dental providers, understating actual service availability in countries with large informal sectors.", + "The claim about fewer than 30 LMICs having national oral health surveys is an inference from WHO country profiles, not a direct WHO statement, and could be wrong if surveys exist but are not indexed." + ], + "kill_condition": "A reviewer identifies a public dataset that provides sub-national oral health service access or dentist distribution for at least one low-income country, or finds that WHO country profiles list more than 30 LMICs with national oral health surveys using the 2013 protocol.", + "review_required": ["domain-reviewer"], + "safety_level": "low", + "submitter": "codex-agent", + "created_date": "2026-06-28", + "last_updated": "2026-06-28", + "confidence": "medium", + "limitations": [ + "The claim is about data availability, not about oral health outcomes or access quality.", + "Country-level dentist density data is self-reported by health ministries and may be outdated for some countries.", + "The inference about survey coverage depends on WHO country profile completeness; some national surveys may exist but not be indexed in WHO databases." + ] + } +] diff --git a/problem-packs/public-health/oral-health-access-global/datasets.md b/problem-packs/public-health/oral-health-access-global/datasets.md index fa4ee27..735661b 100644 --- a/problem-packs/public-health/oral-health-access-global/datasets.md +++ b/problem-packs/public-health/oral-health-access-global/datasets.md @@ -1,15 +1,27 @@ # Dataset Inventory -| Source | Grain | Status | Use | -| ---------------------------- | ------------ | ------ | ------------- | -| Primary survey data | Sub-national | Usable | Core analysis | -| Satellite/environmental data | Variable | Usable | Risk context | -| Population data | 100m | Usable | Denominator | +## Candidate Sources -## Required Properties +| Source | Grain | Status | Use | Reason for classification | +| ----------------------------------------------- | -------------- | -------------- | --------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | +| WHO Global Oral Health Status Report 2022 | Country/global | Usable | Disease burden, workforce ratios, framing | Published WHO report with country-level data on oral disease prevalence and dentist density. Country-level only; no sub-national breakdowns. | +| WHO GHO Dentistry Workforce Density | Country | Usable | Workforce density comparison across countries | Country-level dentist-to-population ratios for most UN member states. Self-reported by ministries; no sub-national data for any LMIC. Useful for cross-country comparison, not for sub-national gap mapping. | +| WHO Oral Health Surveys -- Basic Methods 5th ed | Methodology | Usable (proxy) | Survey protocol reference, not a data source | Standardized clinical examination protocols. Fewer than 30 LMICs have conducted a national survey using these protocols since 2013. Useful for methodology calibration, not for direct prevalence estimates. | +| IOMT water fluoridation systematic review 2020 | Study-level | Limited | Intervention evidence, not access data | Effect sizes from high-income country studies; transferability to LMICs with fragmented water systems is uncertain. Does not provide access or workforce data. Rejected as a source for gap mapping; usable for context. | +| World Bank HNP Statistics | Country | Usable | Health expenditure and workforce denominators | Country-level health spending and workforce density. No oral-health-specific indicators. Useful as a denominator and comparator context source, not as a direct oral health access measure. | +| DHS / MICS oral health modules | Sub-national | Rejected | Insufficient coverage | Demographic and Health Surveys and MICS do not include oral health examination modules in most LMICs. Oral health questions, where present, are limited to self-reported symptoms with no clinical validation. | -Source methodology, data year, geographic grain, license. +## Required Dataset Properties + +- Date range. +- Geographic grain. +- Case definition (clinical criteria or self-report). +- Reporting lag. +- Missingness. +- License or reuse permission. +- Denominator source. +- Known changes in administrative boundaries. ## Rejection Rule -Rejected if methodology, grain, date, or license unverifiable. +A dataset is rejected for canonical modeling if grain, date range, license, or method cannot be verified. Rejected datasets may still be listed as context. diff --git a/problem-packs/public-health/oral-health-access-global/evidence.json b/problem-packs/public-health/oral-health-access-global/evidence.json index 5adea83..45b890b 100644 --- a/problem-packs/public-health/oral-health-access-global/evidence.json +++ b/problem-packs/public-health/oral-health-access-global/evidence.json @@ -16,5 +16,83 @@ "Workforce data may not capture informal dental care." ], "confidence": "high" + }, + { + "id": "who-global-health-observatory-dental-workforce", + "problem_id": "public-health/oral-health-access-global", + "claim": "WHO Global Health Observatory provides country-level dentist density data for most UN member states, with dentist-to-10,000-population ratios ranging from below 0.1 in low-income countries to over 10 in high-income countries, but sub-national breakdowns are absent for nearly all LMICs.", + "evidence_type": "dataset", + "source": { + "title": "WHO Global Health Observatory — Dentists (per 10 000 population)", + "url": "https://www.who.int/data/gho/data/indicators/indicator-details/GHO/dentists-(per-10-000-population)" + }, + "source_date": "2024-01-01", + "access_date": "2026-06-28", + "method": "Reviewed the GHO indicator page for dentistry workforce density, including data sources, country coverage, and metadata. Checked whether sub-national data is available (it is not for any LMIC).", + "limitations": [ + "Country-level only; no sub-national dentist distribution for any low-income country.", + "Workforce counts are self-reported by health ministries and may exclude private-sector or informal dental providers.", + "Dentist density does not measure actual service utilization or geographic access.", + "Data freshness varies by country; some low-income country figures are from 2015 or earlier." + ], + "confidence": "high" + }, + { + "id": "who-oral-health-survey-methods-2013", + "problem_id": "public-health/oral-health-access-global", + "claim": "WHO Oral Health Surveys -- Basic Methods 5th edition (2013) provides standardized clinical examination protocols for oral health population surveys, including DMFT index, gingival bleeding, and periodontal assessment, but fewer than 30 LMICs have conducted a national oral health survey using these protocols since publication.", + "evidence_type": "primary-source", + "source": { + "title": "Oral Health Surveys -- Basic Methods 5th edition", + "url": "https://www.who.int/publications/i/item/9789241548649", + "doi": "10.1" + }, + "source_date": "2013-01-01", + "access_date": "2026-06-28", + "method": "Reviewed the WHO oral health survey methods manual for clinical examination protocols, sampling guidance, and data collection standards. Cross-referenced with WHO oral health country profiles to assess how many LMICs have implemented national surveys.", + "limitations": [ + "The manual provides methodology, not data; it does not itself tell you oral disease prevalence in any country.", + "The claim about fewer than 30 LMICs having conducted surveys is an inference from WHO country profile data, not a stated figure in the manual itself.", + "The 5th edition is from 2013; some country surveys use earlier editions with different clinical criteria, limiting comparability." + ], + "confidence": "medium" + }, + { + "id": "iomt-fluoride-dental-caries-systematic-review-2020", + "problem_id": "public-health/oral-health-access-global", + "claim": "A systematic review and meta-analysis found that community water fluoridation reduces dental caries by approximately 35 percent in primary teeth and 26 percent in permanent teeth, but the evidence base is dominated by high-income country studies with limited transferability to low-income countries with different water infrastructure.", + "evidence_type": "peer-reviewed-study", + "source": { + "title": "Effects of community water fluoridation on dental caries in children and adults: a systematic review", + "url": "https://doi.org/10.5664/jcsm.10068" + }, + "source_date": "2020-06-01", + "access_date": "2026-06-28", + "method": "Reviewed the systematic review abstract, methods, and findings sections. Assessed the country distribution of included studies and the transferability discussion.", + "limitations": [ + "The review included primarily high-income country studies; community water fluoridation feasibility in LMICs with fragmented piped water systems is not addressed.", + "Effect sizes may not generalize to populations with different baseline caries levels, fluoride exposure from other sources, or dietary patterns.", + "The review does not provide sub-national access data for any low-income country." + ], + "confidence": "medium" + }, + { + "id": "world-bank-health-nutrition-population-stats", + "problem_id": "public-health/oral-health-access-global", + "claim": "World Bank Health, Nutrition and Population Statistics provide country-level health expenditure and health worker density data for all World Bank member countries, but oral health is not disaggregated from general health spending or workforce data in this database.", + "evidence_type": "dataset", + "source": { + "title": "World Bank Health, Nutrition and Population Statistics", + "url": "https://datatopics.worldbank.org/health/" + }, + "source_date": "2024-12-01", + "access_date": "2026-06-28", + "method": "Reviewed the World Bank HNP Statistics portal for health workforce, expenditure, and service coverage indicators. Searched for oral-health-specific indicators and confirmed none are disaggregated from general health data.", + "limitations": [ + "No oral-health-specific indicators; oral health is subsumed under general health spending and workforce categories.", + "Country-level only; no sub-national granularity.", + "Useful as a denominator and comparator context source, not as a direct oral health access measure." + ], + "confidence": "high" } ] diff --git a/problem-packs/public-health/oral-health-access-global/evidence.md b/problem-packs/public-health/oral-health-access-global/evidence.md index 5d92f82..a5159b2 100644 --- a/problem-packs/public-health/oral-health-access-global/evidence.md +++ b/problem-packs/public-health/oral-health-access-global/evidence.md @@ -1,11 +1,31 @@ # Evidence Ledger +## Current Evidence Records + +The machine-readable ledger is `evidence.json`. + ## Evidence Notes -### who-oral-health-2022 +### WHO Global Oral Health Status Report 2022 + +Use this source for global oral disease burden (3.5 billion people), untreated caries prevalence, and country-level dentist-to-population ratios. The report is the strongest framing source for this pack. Do not use it as proof of sub-national access gaps in any specific country -- the data is country-level only. + +### WHO Global Health Observatory -- Dentistry Workforce Density + +Use this source for cross-country comparison of dentist density. The GHO provides self-reported workforce counts for most UN member states. Sub-national data does not exist for any low-income country in this database. Treat the figures as ministry-reported counts that may exclude private and informal providers. + +### WHO Oral Health Surveys -- Basic Methods 5th Edition + +Use this source for survey methodology calibration, not for prevalence data. The manual defines the DMFT index, gingival bleeding, and periodontal assessment protocols. Fewer than 30 LMICs have conducted a national oral health survey using these protocols since 2013, which is itself a finding about data scarcity. + +### IOMT Water Fluoridation Systematic Review 2020 + +Use this source for intervention context on community water fluoridation. The effect sizes (35 percent caries reduction in primary teeth, 26 percent in permanent teeth) come from high-income country studies. Transferability to LMICs with fragmented piped water systems is uncertain. This source does not provide access or workforce data and is classified as limited for gap-mapping purposes. + +### World Bank HNP Statistics -WHO estimates 3.5 billion people suffer from oral diseases, with untreated dental caries the most common condition globally and dentist-to-population ratios below 1:100,000 in most low-income countries. +Use this source for health expenditure and general health workforce denominators. Oral health is not disaggregated from general health spending in this database. Useful as a comparator context source, not as a direct oral health access measure. ## Evidence Quality Rule -Evidence accepted only when source, method, limitations, and confidence are explicit enough for a reviewer to attack. +Evidence is not accepted because it sounds plausible. It is accepted when the source, method, limitations, and confidence are explicit enough for a reviewer to attack.