Jack W Baker
Biographic Data
| ID | 6451180 |
|---|---|
| NAME | Jack W Baker |
| GIVEN NAMES | Jack W |
| FAMILY NAME | Baker |
| SIGNATURE | BAKER J W |
| AFFILIATIONS | Stanford University |
| ORCID | 0000-0003-2744-9599 |
| VERIFIED | Yes |
| TOTAL WORKS | 25 |
| TOTAL CITATIONS | 39 |
| AUTHOR COUNT | 25 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2005 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 4 |
Socio-technical regional disaster recovery modeling using generative LLM-based agents
Understanding and simulating the interaction between people and infrastructure is critical for planning and managing recovery after disasters. Human decision-making in the post-disaster context is often simulated using agent-based models, where household behavior is represented using decision rules. Such rules can be difficult to calibrate due to data scarcity and become intractable as the number of parameters that affect households increases. Th…
Refined Adaptive Regional Input–Output Model
The Adaptive Regional Input–Output (ARIO) model is popular for quantifying indirect economic losses, which stem from business and supply chain interruption. However, refining this model to study new contexts is challenging in its basic form due to low-resolution modeling of behavioral parameters and temporally static reconstruction rates. This paper presents a refined ARIO, or R-ARIO model that incorporates dynamic reconstruction rates, sector-le…
Post-disaster housing recovery estimation
Multi-regional economic recovery simulation using an Adaptive Regional Input–Output (Ario) framework
Probabilistic Regional Liquefaction Hazard and Risk Analysis
The impact of liquefaction on a regional scale is not well understood or modeled with traditional approaches. This paper presents a method to quantitatively assess liquefaction hazard and risk on a regional scale, accounting for uncertainties in soil properties, groundwater conditions, ground-shaking parameters, and empirical liquefaction potential index equations. The regional analysis is applied to a case study to calculate regional occurrence …
Uncovering Drivers of Atmospheric River Flood Damage Using Interpretable Machine Learning
The intensity of an atmospheric river (AR) is only one of the factors influencing the damage it will cause. We use random forest models fit to hazard, exposure, and vulnerability data at different spatial and temporal scales in California to predict the probability that a given AR event will cause flood damage, as measured by National Flood Insurance Program (NFIP) claims. We first demonstrate the usefulness of data-driven models and interpretabl…
Household Displacement and Return in Disasters
Household displacement following disasters has become endemic in many areas worldwide, affecting at least 265 million people between 2008 and 2018. Although this figure includes short-term and potentially life-saving evacuations, there is ample evidence that not all households return after the emergency phase. Protracted displacement is associated with particularly negative consequences for the affected households and community. Yet, existing dat…
Quantifying the fragility of coral reefs to hurricane impacts
Ecosystems like coral reefs mitigate rising coastal flood risks, but investments into their conservation remain low relative to the investments into engineered risk-mitigation structures. One reason is that quantifying the risk-reduction benefits of coral reefs requires an estimate of their fragility to severe stresses. Engineered structures typically have associated fragility functions which predict the probability of exceeding a damage state wi…
Boosted Regression Trees for Small-Area Population Forecasting
Integrating Place Attachment into Housing Recovery Simulations to Estimate Population Losses
Following a disaster, residents of a community may be displaced from their damaged homes, leading to expensive and lengthy disruption, with many choosing to move away permanently. Population losses may hinder recovery and exacerbate inequalities across neighborhoods. This study considered household place attachment and identified groups with low place attachment along with expensive and slow postdisaster recovery. We developed a framework to inte…
Efficacy of Damage Data Integration
Weeks after a disaster, crucial response and recovery decisions require information on the locations and scale of building damage. Geostatistical data integration methods estimate post-disaster damage by calibrating engineering forecasts or remote sensing-derived proxies with limited field measurements. These methods are meant to adapt to building damage and post-earthquake data sources that vary depending on location, but their performances acro…
Smote–Lasso Model of Business Recovery over Time
A methodology is presented to combine the synthetic minority oversampling technique and the least absolute shrinkage and selection operator to analyze survey data and identify business characteristics correlated with recovery within selected time windows. The methodology addresses challenges that arise when data is imbalanced and predictors are collinear. A case study using data from a survey of business recovery conducted one year after the 2011…
Using Synthetic Adjustments and Controlling to Improve County Population Forecasts from the Hamilton–Perry Method
Tayman and Swanson (J Popul Res 34(3):209–231, 2017) found in Washington State counties that a forecast based on the Hamilton–Perry method using a synthetic adjustment (SYN) of cohort change ratios and child-woman ratios had greater accuracy and less bias compared to forecasts holding these ratios constant (CONST). In this paper, we assess the robustness of SYN’s efficacy by evaluating forecast accuracy, bias, and distributional error across age …
The Accuracy of Hamilton–Perry Population Projections for Census Tracts in the United States
An exploration of school mobility
This study explored negative emotional, behavioral, and academic performance outcomes for highly mobile students and potential protective factors. Participants were fourth and fifth‐grade students ( N = 647, 51% male) from three schools with low socioeconomic status, highly mobile student populations within a large, suburban school district in the midwestern United States. Data were collected through student self‐report surveys, teacher‐report su…
Quantification of disaster impacts through household well-being losses
Estimating the underlying infant mortality rates for small populations
Birth weight predicted baseline muscular efficiency, but not response of energy expenditure to calorie restriction
Birth size did not influence the sensitivity of metabolic demands to fasting-neither at rest nor during activity. Moreover, small birth size predicted a reduction in the efficiency with which muscles convert energy expended into work accomplished. These results do not support the ascription of adaptive function to phenotypes associated with small birth size. © 2015 Wiley Periodicals, Inc. Am. J. Hum. Biol. 28:484-492, 2016. © 2015 Wiley Periodica…
Spatial weighting improves accuracy in small-area demographic forecasts of urban census tract populations
A Comparative Evaluation of Error and Bias in Census Tract-Level Age/Sex-Specific Population Estimates
Low birth weight does not predict the ontogeny of relative leg length of infants and children
Previous research links both low birth weight (LBW) and relative leg length (RLL) to a similar set of adult pathologies, including type II diabetes, coronary vascular disease, and some cancers. Historically, LBW has been frequently used as a broad indicator of the quality of the intrauterine environment, while RLL has been considered a sensitive measure of childhood environmental quality. While these observations have been taken to suggest that t…
The impact of incomplete geocoding on small area population estimates
Brains versus brawn
The Barker model of the in utero origins of diminished muscle mass in those born small invokes the adaptive “sparing” of brain tissue development at the expense of muscle. Though compelling, to date this model has not been directly tested. This article develops an allometric framework for testing the principal prediction of the Barker model—that among those born small muscle mass is sacrificed to spare brain growth—then evaluates this hypothesis …
Developmental plasticity in fat patterning of Ache children in response to variation in interbirth intervals
A firm link between small size at birth and later more centralized fat patterning has been established in previous research. Relationships between shortened interbirth intervals and small size at birth suggest that maternal energetic prioritization may be an important, but unexplored determinant of offspring fat patterning. Potential adaptive advantages to centralized fat storage (Baker et al., 2008: In: Trevathan W, McKenna J, Smith EO, editors.…
Statistical methods for bioarchaeology
The Accuracy of Hamilton–Perry Population Projections for Census Tracts in the United States
Spatial weighting improves accuracy in small-area demographic forecasts of urban census tract populations
Statistical methods for bioarchaeology
Using Synthetic Adjustments and Controlling to Improve County Population Forecasts from the Hamilton–Perry Method
Tayman and Swanson (J Popul Res 34(3):209–231, 2017) found in Washington State counties that a forecast based on the Hamilton–Perry method using a synthetic adjustment (SYN) of cohort change ratios and child-woman ratios had greater accuracy and less bias compared to forecasts holding these ratios constant (CONST). In this paper, we assess the robustness of SYN’s efficacy by evaluating forecast accuracy, bias, and distributional error across age …
Low birth weight does not predict the ontogeny of relative leg length of infants and children
Previous research links both low birth weight (LBW) and relative leg length (RLL) to a similar set of adult pathologies, including type II diabetes, coronary vascular disease, and some cancers. Historically, LBW has been frequently used as a broad indicator of the quality of the intrauterine environment, while RLL has been considered a sensitive measure of childhood environmental quality. While these observations have been taken to suggest that t…
A Comparative Evaluation of Error and Bias in Census Tract-Level Age/Sex-Specific Population Estimates
Quantification of disaster impacts through household well-being losses
Boosted Regression Trees for Small-Area Population Forecasting
Estimating the underlying infant mortality rates for small populations
The impact of incomplete geocoding on small area population estimates
Statistical methods for bioarchaeology
Developmental plasticity in fat patterning of Ache children in response to variation in interbirth intervals
A firm link between small size at birth and later more centralized fat patterning has been established in previous research. Relationships between shortened interbirth intervals and small size at birth suggest that maternal energetic prioritization may be an important, but unexplored determinant of offspring fat patterning. Potential adaptive advantages to centralized fat storage (Baker et al., 2008: In: Trevathan W, McKenna J, Smith EO, editors.…
Brains versus brawn
The Barker model of the in utero origins of diminished muscle mass in those born small invokes the adaptive “sparing” of brain tissue development at the expense of muscle. Though compelling, to date this model has not been directly tested. This article develops an allometric framework for testing the principal prediction of the Barker model—that among those born small muscle mass is sacrificed to spare brain growth—then evaluates this hypothesis …
The impact of incomplete geocoding on small area population estimates
Low birth weight does not predict the ontogeny of relative leg length of infants and children
Previous research links both low birth weight (LBW) and relative leg length (RLL) to a similar set of adult pathologies, including type II diabetes, coronary vascular disease, and some cancers. Historically, LBW has been frequently used as a broad indicator of the quality of the intrauterine environment, while RLL has been considered a sensitive measure of childhood environmental quality. While these observations have been taken to suggest that t…
A Comparative Evaluation of Error and Bias in Census Tract-Level Age/Sex-Specific Population Estimates
Spatial weighting improves accuracy in small-area demographic forecasts of urban census tract populations
Birth weight predicted baseline muscular efficiency, but not response of energy expenditure to calorie restriction
Birth size did not influence the sensitivity of metabolic demands to fasting-neither at rest nor during activity. Moreover, small birth size predicted a reduction in the efficiency with which muscles convert energy expended into work accomplished. These results do not support the ascription of adaptive function to phenotypes associated with small birth size. © 2015 Wiley Periodicals, Inc. Am. J. Hum. Biol. 28:484-492, 2016. © 2015 Wiley Periodica…
Estimating the underlying infant mortality rates for small populations
An exploration of school mobility
This study explored negative emotional, behavioral, and academic performance outcomes for highly mobile students and potential protective factors. Participants were fourth and fifth‐grade students ( N = 647, 51% male) from three schools with low socioeconomic status, highly mobile student populations within a large, suburban school district in the midwestern United States. Data were collected through student self‐report surveys, teacher‐report su…
Quantification of disaster impacts through household well-being losses
Smote–Lasso Model of Business Recovery over Time
A methodology is presented to combine the synthetic minority oversampling technique and the least absolute shrinkage and selection operator to analyze survey data and identify business characteristics correlated with recovery within selected time windows. The methodology addresses challenges that arise when data is imbalanced and predictors are collinear. A case study using data from a survey of business recovery conducted one year after the 2011…
Using Synthetic Adjustments and Controlling to Improve County Population Forecasts from the Hamilton–Perry Method
Tayman and Swanson (J Popul Res 34(3):209–231, 2017) found in Washington State counties that a forecast based on the Hamilton–Perry method using a synthetic adjustment (SYN) of cohort change ratios and child-woman ratios had greater accuracy and less bias compared to forecasts holding these ratios constant (CONST). In this paper, we assess the robustness of SYN’s efficacy by evaluating forecast accuracy, bias, and distributional error across age …
The Accuracy of Hamilton–Perry Population Projections for Census Tracts in the United States
Integrating Place Attachment into Housing Recovery Simulations to Estimate Population Losses
Following a disaster, residents of a community may be displaced from their damaged homes, leading to expensive and lengthy disruption, with many choosing to move away permanently. Population losses may hinder recovery and exacerbate inequalities across neighborhoods. This study considered household place attachment and identified groups with low place attachment along with expensive and slow postdisaster recovery. We developed a framework to inte…
Efficacy of Damage Data Integration
Weeks after a disaster, crucial response and recovery decisions require information on the locations and scale of building damage. Geostatistical data integration methods estimate post-disaster damage by calibrating engineering forecasts or remote sensing-derived proxies with limited field measurements. These methods are meant to adapt to building damage and post-earthquake data sources that vary depending on location, but their performances acro…
Quantifying the fragility of coral reefs to hurricane impacts
Ecosystems like coral reefs mitigate rising coastal flood risks, but investments into their conservation remain low relative to the investments into engineered risk-mitigation structures. One reason is that quantifying the risk-reduction benefits of coral reefs requires an estimate of their fragility to severe stresses. Engineered structures typically have associated fragility functions which predict the probability of exceeding a damage state wi…
Boosted Regression Trees for Small-Area Population Forecasting
Post-disaster housing recovery estimation
Multi-regional economic recovery simulation using an Adaptive Regional Input–Output (Ario) framework
Probabilistic Regional Liquefaction Hazard and Risk Analysis
The impact of liquefaction on a regional scale is not well understood or modeled with traditional approaches. This paper presents a method to quantitatively assess liquefaction hazard and risk on a regional scale, accounting for uncertainties in soil properties, groundwater conditions, ground-shaking parameters, and empirical liquefaction potential index equations. The regional analysis is applied to a case study to calculate regional occurrence …
Uncovering Drivers of Atmospheric River Flood Damage Using Interpretable Machine Learning
The intensity of an atmospheric river (AR) is only one of the factors influencing the damage it will cause. We use random forest models fit to hazard, exposure, and vulnerability data at different spatial and temporal scales in California to predict the probability that a given AR event will cause flood damage, as measured by National Flood Insurance Program (NFIP) claims. We first demonstrate the usefulness of data-driven models and interpretabl…
Household Displacement and Return in Disasters
Household displacement following disasters has become endemic in many areas worldwide, affecting at least 265 million people between 2008 and 2018. Although this figure includes short-term and potentially life-saving evacuations, there is ample evidence that not all households return after the emergency phase. Protracted displacement is associated with particularly negative consequences for the affected households and community. Yet, existing dat…
Refined Adaptive Regional Input–Output Model
The Adaptive Regional Input–Output (ARIO) model is popular for quantifying indirect economic losses, which stem from business and supply chain interruption. However, refining this model to study new contexts is challenging in its basic form due to low-resolution modeling of behavioral parameters and temporally static reconstruction rates. This paper presents a refined ARIO, or R-ARIO model that incorporates dynamic reconstruction rates, sector-le…
Socio-technical regional disaster recovery modeling using generative LLM-based agents
Understanding and simulating the interaction between people and infrastructure is critical for planning and managing recovery after disasters. Human decision-making in the post-disaster context is often simulated using agent-based models, where household behavior is represented using decision rules. Such rules can be difficult to calibrate due to data scarcity and become intractable as the number of parameters that affect households increases. Th…
Geography (13 works) · Demography (12 works) · Computer Science (11 works) · Population (11 works) · Statistics (9 works) · Demography (8 works) · Mathematics (8 works) · demographic modeling and climate adaptation (7 works) · Engineering (7 works) · Sociology (7 works)