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On Setyembre 14, 2025 nang 8:00:15 PM UTC,
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Deleted resource Enhanced Narrative Analysis for Arctic Infrastructure from Sites & Stories Interactive for CRC Paper
| f | 1 | { | f | 1 | { |
| 2 | "author": "Suzanne Pierce", | 2 | "author": "Suzanne Pierce", | ||
| 3 | "author_email": "spierce@tacc.utexas.edu", | 3 | "author_email": "spierce@tacc.utexas.edu", | ||
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| 8 | "license_id": "cc-by", | 8 | "license_id": "cc-by", | ||
| 9 | "license_title": "Creative Commons Attribution", | 9 | "license_title": "Creative Commons Attribution", | ||
| 10 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | 10 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | ||
| 11 | "maintainer": "Suzanne Pierce", | 11 | "maintainer": "Suzanne Pierce", | ||
| 12 | "maintainer_email": "spierce@tacc.utexas.edu", | 12 | "maintainer_email": "spierce@tacc.utexas.edu", | ||
| 13 | "metadata_created": "2025-09-14T17:58:47.557685", | 13 | "metadata_created": "2025-09-14T17:58:47.557685", | ||
| n | 14 | "metadata_modified": "2025-09-14T19:57:27.871067", | n | 14 | "metadata_modified": "2025-09-14T20:00:15.016789", |
| 15 | "name": "sites-stories-interactive-for-crc-paper", | 15 | "name": "sites-stories-interactive-for-crc-paper", | ||
| 16 | "notes": "Results: Community-Informed Climate Impact Assessment of | 16 | "notes": "Results: Community-Informed Climate Impact Assessment of | ||
| 17 | Nunapitchuk, Alaska\r\n\r\nThis is a preliminary analysis and | 17 | Nunapitchuk, Alaska\r\n\r\nThis is a preliminary analysis and | ||
| 18 | interactive site combining results of Arctic Infrastructure Analyses | 18 | interactive site combining results of Arctic Infrastructure Analyses | ||
| 19 | that link narrative interview information with on the ground | 19 | that link narrative interview information with on the ground | ||
| 20 | environmental information collected using drone sensors. The study | 20 | environmental information collected using drone sensors. The study | ||
| 21 | presents a mixed-methods analysis integrating stakeholder interviews | 21 | presents a mixed-methods analysis integrating stakeholder interviews | ||
| 22 | (n=7, ages 43-80) with geospatial data to assess climate-induced | 22 | (n=7, ages 43-80) with geospatial data to assess climate-induced | ||
| 23 | infrastructure vulnerabilities in Nunapitchuk, Alaska. Through | 23 | infrastructure vulnerabilities in Nunapitchuk, Alaska. Through | ||
| 24 | systematic coding of interview transcripts, we identified 47 | 24 | systematic coding of interview transcripts, we identified 47 | ||
| 25 | references to permafrost degradation, representing the dominant | 25 | references to permafrost degradation, representing the dominant | ||
| 26 | environmental concern across all stakeholder groups. The analysis | 26 | environmental concern across all stakeholder groups. The analysis | ||
| 27 | revealed critical infrastructure failures affecting 38 documented | 27 | revealed critical infrastructure failures affecting 38 documented | ||
| 28 | structures, with differential subsidence rates showing south-facing | 28 | structures, with differential subsidence rates showing south-facing | ||
| 29 | foundations degrading 40% faster than north-facing | 29 | foundations degrading 40% faster than north-facing | ||
| 30 | structures.\r\n\r\nOur Scientific Variable Object (SVO) framework | 30 | structures.\r\n\r\nOur Scientific Variable Object (SVO) framework | ||
| 31 | mapped nine quantifiable metrics to stakeholder priorities, revealing | 31 | mapped nine quantifiable metrics to stakeholder priorities, revealing | ||
| 32 | high concordance (>80%) between elder traditional knowledge and | 32 | high concordance (>80%) between elder traditional knowledge and | ||
| 33 | scientific measurements for permafrost thaw rates and ground | 33 | scientific measurements for permafrost thaw rates and ground | ||
| 34 | subsidence indicators. Water quality assessments detected arsenic | 34 | subsidence indicators. Water quality assessments detected arsenic | ||
| 35 | concentrations downstream from waste facilities, corroborating | 35 | concentrations downstream from waste facilities, corroborating | ||
| 36 | community-reported health concerns including unprecedented cancer | 36 | community-reported health concerns including unprecedented cancer | ||
| 37 | clusters and first-time waterborne illnesses among lifelong | 37 | clusters and first-time waterborne illnesses among lifelong | ||
| 38 | residents.\r\n\r\nThe perceived environmental change trajectory, | 38 | residents.\r\n\r\nThe perceived environmental change trajectory, | ||
| 39 | validated through temporal analysis spanning 1920-2024, demonstrates | 39 | validated through temporal analysis spanning 1920-2024, demonstrates | ||
| 40 | accelerating degradation with ground stability declining from 95% | 40 | accelerating degradation with ground stability declining from 95% | ||
| 41 | (1970s) to 30% (2020s). Multiple stakeholders independently estimated | 41 | (1970s) to 30% (2020s). Multiple stakeholders independently estimated | ||
| 42 | a 3-5 year window before complete infrastructure failure, aligning | 42 | a 3-5 year window before complete infrastructure failure, aligning | ||
| 43 | with geotechnical projections showing active layer depths increasing | 43 | with geotechnical projections showing active layer depths increasing | ||
| 44 | at 12cm/year.\r\n\r\nEconomic impact analysis revealed a 900% increase | 44 | at 12cm/year.\r\n\r\nEconomic impact analysis revealed a 900% increase | ||
| 45 | in energy costs over one generation ($20/barrel to $190/month), | 45 | in energy costs over one generation ($20/barrel to $190/month), | ||
| 46 | threatening community sustainability. The 3D point cloud visualization | 46 | threatening community sustainability. The 3D point cloud visualization | ||
| 47 | captured 2.3km\u00b2 of riverbank terrain at 15-point/m\u00b2 density, | 47 | captured 2.3km\u00b2 of riverbank terrain at 15-point/m\u00b2 density, | ||
| 48 | documenting erosion rates of 2.5m/year and permafrost-related surface | 48 | documenting erosion rates of 2.5m/year and permafrost-related surface | ||
| 49 | deformation patterns.\r\n\r\nCritical findings indicate immediate | 49 | deformation patterns.\r\n\r\nCritical findings indicate immediate | ||
| 50 | federal intervention is required, with $11 million already allocated | 50 | federal intervention is required, with $11 million already allocated | ||
| 51 | for waste management upgrades. The convergence of traditional | 51 | for waste management upgrades. The convergence of traditional | ||
| 52 | knowledge with quantitative measurements strengthens the validity of | 52 | knowledge with quantitative measurements strengthens the validity of | ||
| 53 | relocation timelines. This integrated assessment framework provides a | 53 | relocation timelines. This integrated assessment framework provides a | ||
| 54 | replicable methodology for climate impact evaluation in Arctic | 54 | replicable methodology for climate impact evaluation in Arctic | ||
| 55 | communities, demonstrating the value of incorporating indigenous | 55 | communities, demonstrating the value of incorporating indigenous | ||
| 56 | knowledge systems into engineering assessments for infrastructure | 56 | knowledge systems into engineering assessments for infrastructure | ||
| 57 | resilience planning.\r\n\r\nComparison: AI vs Human Coding AnalysisKey | 57 | resilience planning.\r\n\r\nComparison: AI vs Human Coding AnalysisKey | ||
| 58 | Differences: \r\n\r\nThe AI analysis identified significantly more | 58 | Differences: \r\n\r\nThe AI analysis identified significantly more | ||
| 59 | thematic references (215 total) compared to human coding (19 entries), | 59 | thematic references (215 total) compared to human coding (19 entries), | ||
| 60 | with AI emphasizing permafrost degradation as the primary concern | 60 | with AI emphasizing permafrost degradation as the primary concern | ||
| 61 | while human coders focused more granularly on specific infrastructure | 61 | while human coders focused more granularly on specific infrastructure | ||
| 62 | issues like boardwalks and dump management. Human coding showed the | 62 | issues like boardwalks and dump management. Human coding showed the | ||
| 63 | City Manager contributing 58% of coded entries, suggesting more | 63 | City Manager contributing 58% of coded entries, suggesting more | ||
| 64 | detailed attention to administrative perspectives, whereas AI analysis | 64 | detailed attention to administrative perspectives, whereas AI analysis | ||
| 65 | distributed concerns more evenly across stakeholder groups. The AI | 65 | distributed concerns more evenly across stakeholder groups. The AI | ||
| 66 | approach captured broader thematic patterns and frequencies, while | 66 | approach captured broader thematic patterns and frequencies, while | ||
| 67 | human coding provided more precise, quote-specific categorizations | 67 | human coding provided more precise, quote-specific categorizations | ||
| 68 | with detailed contextual understanding. Both approaches identified | 68 | with detailed contextual understanding. Both approaches identified | ||
| 69 | waste management and infrastructure failure as critical issues, but | 69 | waste management and infrastructure failure as critical issues, but | ||
| 70 | differed in their emphasis on cultural preservation (AI) versus | 70 | differed in their emphasis on cultural preservation (AI) versus | ||
| 71 | practical infrastructure solutions (human coders).Similarities: Both | 71 | practical infrastructure solutions (human coders).Similarities: Both | ||
| 72 | identified dump/waste management and infrastructure problems related | 72 | identified dump/waste management and infrastructure problems related | ||
| 73 | to ground instability as critical issues, recognized water quality | 73 | to ground instability as critical issues, recognized water quality | ||
| 74 | concerns, and captured the urgency of the situation requiring | 74 | concerns, and captured the urgency of the situation requiring | ||
| 75 | immediate intervention.", | 75 | immediate intervention.", | ||
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| 79 | "approval_status": "approved", | 79 | "approval_status": "approved", | ||
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| 83 | "image_url": "2025-09-10-170732.810429SubarcticAnnotationNNA.png", | 83 | "image_url": "2025-09-10-170732.810429SubarcticAnnotationNNA.png", | ||
| 84 | "is_organization": true, | 84 | "is_organization": true, | ||
| 85 | "name": "arctic-infrastructure", | 85 | "name": "arctic-infrastructure", | ||
| 86 | "state": "active", | 86 | "state": "active", | ||
| 87 | "title": "Arctic Infrastructure", | 87 | "title": "Arctic Infrastructure", | ||
| 88 | "type": "organization" | 88 | "type": "organization" | ||
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