title: Harnessing Indigenous Tweets: The Reo Maori Twitter corpus

authors: Trye, David

subjects: Science & Technology

abstract: Te reo Māori, the Indigenous language of Aotearoa New Zealand, is a distinctive feature of the nation’s cultural heritage. This paper documents our efforts to build a corpus of 79,000 Māori-language tweets using computational methods. The Reo Māori Twitter (RMT) Corpus was created by targeting Māori-language users identified by the Indigenous Tweets website, pre-processing their data and filtering out non-Māori tweets, together with other sources of noise. Our motivation for creating such a resource is three-fold: (1) it serves as a rich and unique dataset for linguistic analysis of te reo Māori on social media; (2) it can be used as training data to develop and augment Natural Language Processing (NLP) tools with robust, real-world Māori-language applications; and (3) it will potentially promote awareness of, and encourage positive interaction with, the growing community of Māori tweeters, thereby increasing the use and visibility of te reo Māori in an online environment. While the corpus captures data from 2007 to 2020, our analysis shows that the number of tweets in the RMT Corpus peaked in 2014, and the number of active tweeters peaked in 2017, although at least 600 users were still active in 2020. To the best of our knowledge, the RMT Corpus is the largest publicly-available collection of social media data containing (almost) exclusively Māori text, making it a useful resource for language experts, NLP developers and Indigenous researchers alike.

text: Harnessing Indigenous Tweets: The Reo Maori Twitter corpus Te reo Māori, the Indigenous language of Aotearoa New Zealand, is a distinctive feature of the nation’s cultural heritage. This paper documents our efforts to build a corpus of 79,000 Māori-language tweets using computational methods. The Reo Māori Twitter (RMT) Corpus was created by targeting Māori-language users identified by the Indigenous Tweets website, pre-processing their data and filtering out non-Māori tweets, together with other sources of noise. Our motivation for creating such a resource is three-fold: (1) it serves as a rich and unique dataset for linguistic analysis of te reo Māori on social media; (2) it can be used as training data to develop and augment Natural Language Processing (NLP) tools with robust, real-world Māori-language applications; and (3) it will potentially promote awareness of, and encourage positive interaction with, the growing community of Māori tweeters, thereby increasing the use and visibility of te reo Māori in an online environment. While the corpus captures data from 2007 to 2020, our analysis shows that the number of tweets in the RMT Corpus peaked in 2014, and the number of active tweeters peaked in 2017, although at least 600 users were still active in 2020. To the best of our knowledge, the RMT Corpus is the largest publicly-available collection of social media data containing (almost) exclusively Māori text, making it a useful resource for language experts, NLP developers and Indigenous researchers alike.

year: 2022-02-14

title: Kaumatua Mana Motuhake Poi: a study protocol for enhancing wellbeing, socia connectedness and cultural identity for Maori elders

authors: Hokowhitu, Brendan

subjects: Science & Technology

abstract: Background: The Aotearoa New Zealand population is ageing, accompanied by health and social challenges, including significant inequities that exist between Māori and non-Māori around poor ageing and health. Although historically, kaumātua (elder Māori) faced a dominant society that failed to realize their full potential as they age, Māori culture has remained steadfast in upholding elders as cultural/community anchors. Yet, many of today’s kaumātua have experienced ‘cultural dissonance’ as the result of a hegemonic dominant culture subjugating an Indigenous culture, leading to generations of Indigenous peoples compelled or forced to dissociate with their culture. The present research project, Kaumātua Mana Motuhake Pōī (KMMP), comprises two interrelated projects that foreground dimensions of wellbeing within a holistic Te Ao Māori (Māori epistemology) view of wellbeing. Project 1 involves a tuakana-teina/peer educator model approach focused on increasing service access and utilization to support kaumātua with the greatest health and social needs. Project 2 focuses on physical activity and cultural knowledge exchange (including te reo Māori—Māori language) through intergenerational models of learning.

Methods: Both projects have a consistent research design and common set of methods that coalesce around the emphasis on kaupapa kaumātua; research projects led by kaumātua and kaumātua providers that advance better life outcomes for kaumātua and their communities. The research design for each project is a mixed-methods, pretest and two post-test, staggered design with 2–3 providers receiving the approach first and then 2–3 receiving it on a delayed basis. A pre-test (baseline) of all participants will be completed. The approach will then be implemented with the first providers. There will then be a follow-up data collection for all participants (post-test 1). The second providers will then implement the approach, which will be followed by a final data collection for all participants (post-test 2).

Discussion: Two specific outcomes are anticipated from this research; firstly, it is hoped that the research methodology provides a framework for how government agencies, researchers, and relevant sector stakeholders can work with Māori communities. Secondly, the two individual projects will each produce a tangible approach that, it is anticipated, will be cost-effective in enhancing kaumātua hauora and mana motuhake.

text: Kaumatua Mana Motuhake Poi: a study protocol for enhancing wellbeing, socia connectedness and cultural identity for Maori elders Background: The Aotearoa New Zealand population is ageing, accompanied by health and social challenges, including significant inequities that exist between Māori and non-Māori around poor ageing and health. Although historically, kaumātua (elder Māori) faced a dominant society that failed to realize their full potential as they age, Māori culture has remained steadfast in upholding elders as cultural/community anchors. Yet, many of today’s kaumātua have experienced ‘cultural dissonance’ as the result of a hegemonic dominant culture subjugating an Indigenous culture, leading to generations of Indigenous peoples compelled or forced to dissociate with their culture. The present research project, Kaumātua Mana Motuhake Pōī (KMMP), comprises two interrelated projects that foreground dimensions of wellbeing within a holistic Te Ao Māori (Māori epistemology) view of wellbeing. Project 1 involves a tuakana-teina/peer educator model approach focused on increasing service access and utilization to support kaumātua with the greatest health and social needs. Project 2 focuses on physical activity and cultural knowledge exchange (including te reo Māori—Māori language) through intergenerational models of learning.

Methods: Both projects have a consistent research design and common set of methods that coalesce around the emphasis on kaupapa kaumātua; research projects led by kaumātua and kaumātua providers that advance better life outcomes for kaumātua and their communities. The research design for each project is a mixed-methods, pretest and two post-test, staggered design with 2–3 providers receiving the approach first and then 2–3 receiving it on a delayed basis. A pre-test (baseline) of all participants will be completed. The approach will then be implemented with the first providers. There will then be a follow-up data collection for all participants (post-test 1). The second providers will then implement the approach, which will be followed by a final data collection for all participants (post-test 2).

Discussion: Two specific outcomes are anticipated from this research; firstly, it is hoped that the research methodology provides a framework for how government agencies, researchers, and relevant sector stakeholders can work with Māori communities. Secondly, the two individual projects will each produce a tangible approach that, it is anticipated, will be cost-effective in enhancing kaumātua hauora and mana motuhake.

year: 2020-10-02

title: Measuring and modelling estuarine macroalgae blooms and water column nutrients

authors: Port, Marvin Alexander (Alex)

subjects: macroalgae

abstract: This thesis examines the dynamics of estuarine macroalgae blooms of the genus Ulva and the environmental factors controlling them, using process-based mathematical models as well as observation data from Tauranga Harbour (North Island, New Zealand).  
Based on long-term monitoring datasets of water column nutrients, temperature and irradiance, the Ulva tissue nitrogen concentration is modelled using an algebraic short-term equilibrium solution to a classic set of ordinary differential equations describing tissue nutrient dynamics. A detailed sensitivity analysis of this equilibrium solution shows that although the variability in ambient concentration of inorganic nitrogen explains 60% of model output variance, the uncertainty in two of the most influential physiological parameters has a similar magnitude of influence (32% of variance). Repeated calibrations using an algorithm with random starting points and evolutionary adaptions lead to broad and in some cases multimodal distributions of physiological parameters. Although the model performs well in reproducing observations, calibrated parameter values from individual calibrations should therefore not be interpreted as reliable estimates of physiological properties.  
Using a zero-dimensional simulation model of Ulva tissue nitrogen and phosphorus concentrations and biomass, seasonal and long-term population dynamics of Ulva are examined. Calibrating against a combination of all three state variables, long-term tissue nitrogen and biomass dynamics are reproduced well, while the seasonal amplitude of tissue phosphorus variability is underestimated. From the long-term observation datasets, seasonal scenarios are derived based on annual cosine fits to monthly percentiles of the observed forcing data. These scenarios represent above and below average seasons in the environmental conditions of ammonia, nitrate and phosphate concentrations in the water as well as temperature and irradiance. Comparison of the different scenarios points to the inorganic nitrogen concentrations (both ammonia and nitrate) as most influential in determining Ulva seasonal peak biomass and timing.  
To improve upon the existing long-term observations of water column nutrients available for Tauranga Harbour, a sampling programme was designed taking into account the challenges of accurately measuring nutrients in a tidally dominated estuary with complex geometry. Samples were taken at consecutive ebb and flood tides at the same local tidal phase at sites representing distinct subregions within the estuary. Bimonthly samples at eight sites and fortnightly samples at two sites over one year show that the statistical distributions of nutrient fractions vary between sites and between tides. At the estuary mouth, phosphate is exported, while at site further upstream, ammonia and nitrate are exported. Modelling the passive transport of nutrients using a numerical hydrodynamical model shows differences in the connectivity between subregions, and in some cases mid-term upstream transport. The contribution of upstream subregions to individual sites changes rapidly during the tidal cycle, emphasising the importance of the local tidal phase. The data collected may help to improve the sampling design of the long-term monitoring programmes in Tauranga Harbour and provide a more accurate basis for future modelling studies of Ulva population dynamics.

text: Measuring and modelling estuarine macroalgae blooms and water column nutrients This thesis examines the dynamics of estuarine macroalgae blooms of the genus Ulva and the environmental factors controlling them, using process-based mathematical models as well as observation data from Tauranga Harbour (North Island, New Zealand).  
Based on long-term monitoring datasets of water column nutrients, temperature and irradiance, the Ulva tissue nitrogen concentration is modelled using an algebraic short-term equilibrium solution to a classic set of ordinary differential equations describing tissue nutrient dynamics. A detailed sensitivity analysis of this equilibrium solution shows that although the variability in ambient concentration of inorganic nitrogen explains 60% of model output variance, the uncertainty in two of the most influential physiological parameters has a similar magnitude of influence (32% of variance). Repeated calibrations using an algorithm with random starting points and evolutionary adaptions lead to broad and in some cases multimodal distributions of physiological parameters. Although the model performs well in reproducing observations, calibrated parameter values from individual calibrations should therefore not be interpreted as reliable estimates of physiological properties.  
Using a zero-dimensional simulation model of Ulva tissue nitrogen and phosphorus concentrations and biomass, seasonal and long-term population dynamics of Ulva are examined. Calibrating against a combination of all three state variables, long-term tissue nitrogen and biomass dynamics are reproduced well, while the seasonal amplitude of tissue phosphorus variability is underestimated. From the long-term observation datasets, seasonal scenarios are derived based on annual cosine fits to monthly percentiles of the observed forcing data. These scenarios represent above and below average seasons in the environmental conditions of ammonia, nitrate and phosphate concentrations in the water as well as temperature and irradiance. Comparison of the different scenarios points to the inorganic nitrogen concentrations (both ammonia and nitrate) as most influential in determining Ulva seasonal peak biomass and timing.  
To improve upon the existing long-term observations of water column nutrients available for Tauranga Harbour, a sampling programme was designed taking into account the challenges of accurately measuring nutrients in a tidally dominated estuary with complex geometry. Samples were taken at consecutive ebb and flood tides at the same local tidal phase at sites representing distinct subregions within the estuary. Bimonthly samples at eight sites and fortnightly samples at two sites over one year show that the statistical distributions of nutrient fractions vary between sites and between tides. At the estuary mouth, phosphate is exported, while at site further upstream, ammonia and nitrate are exported. Modelling the passive transport of nutrients using a numerical hydrodynamical model shows differences in the connectivity between subregions, and in some cases mid-term upstream transport. The contribution of upstream subregions to individual sites changes rapidly during the tidal cycle, emphasising the importance of the local tidal phase. The data collected may help to improve the sampling design of the long-term monitoring programmes in Tauranga Harbour and provide a more accurate basis for future modelling studies of Ulva population dynamics.

year: 2016