Investigators' Blog

Māori and Pacific Island women in science

Māori and Pacific Island women in science

by | Feb 12, 2018 | | 0 Comments

Before I started working as a research assistant on the Hidden Networks project, the only woman from the history of New Zealand science I could name was Joan Wiffen, the “dinosaur lady” who discovered New Zealand’s first dinosaur fossils in Hawke’s Bay. She was a remarkable woman who contributed much to palaeontology here in New Zealand; she was also, incidentally, very white. I too am outwardly (that is, I pass as) very white. But as a mixed-race woman of Samoan descent, when I started this project I was very interested to learn about the contributions of non-Pākehā – chiefly, Māori and Pacific Island – women to science in Aotearoa. For the purposes of my research, I’ve taken “woman in science” to broadly mean a woman who has made a contribution to science in New Zealand, including both professional scientists with academic backgrounds and amateur scientists who have added to the pool of knowledge in their field, like Joan Wiffen.

The more I researched, the whiter the history of women in science in New Zealand came to look. Unsurprising really: according to Elizabeth McKinley, in 1998 just 1.5% of total employees at seven Crown Research Institutes in New Zealand identified as Māori women; there were none in management positions, and only two scientists. In ‘Finding Matilda’, Kate Hannah notes that “the historiography of science in New Zealand … tends to inadvertently reinforce [the] camouflage” of women. They are marginalized, but not absent: if you go looking, as I have, you’ll find a staggering number of women in New Zealand science from the 14th century to present-day. Yet from the beginnings of European presence in New Zealand, the overwhelming majority of these women were white. A feminist revisionist history of science aims not only to make science less male-centric (i.e. demonstrate, through promotion of women’s work both quantitatively and qualitatively, that science never has been just a man’s world) but also to make it less monochromatic (so to speak), which means celebrating the scientific achievements of brown women in New Zealand’s history, and showing that science never has been just a white world either.

In fact, the first women who made scientific contributions in Aotearoa were not Pākehā but Māori. I was delighted to learn of Whakaotirangi, who in the 1300s “was responsible for safeguarding the seed of the kūmara” as the Tainui Waka journeyed to Waikato. She was the wife of Hoturoa, the leader of the Tainui Waka migration from Hawaiki to Aotearoa, but also an important historical figure in her own right. In ‘Whakaotirangi: A Canoe Tradition’, Diane Gordon-Burns and Rāwiri Taonui explore how her importance has been diminished in post-European contact accounts of the Tainui migration. Tainui and Te Arawa traditions both speak of Whakaotirangi: she appears to be a noble and important ancestor in the history of both iwi. While she is most remembered for bringing kūmara to Waikato, she was also responsible for a number of other plants brought from Hawaiki. On arrival in Waikato, Whakaotirangi built gardens in which she experimented with growing and tending to a variety of plants, both for sustenance and medicinal purposes. She discovered how to make the kūmara, which had come from a much warmer climate, grow in the cooler land her people had settled. Her work was crucial for the establishment of the Tainui people: it provided them with a reliable food supply as they adjusted to life in a new land. She was also involved in commissioning, building and launching the Tainui canoe. Her profile on the Royal Society of New Zealand website, as part of their series 150 Women in 150 Words, credits her as “one of New Zealand’s first scientists”.

Around the middle of the 1400s, another important ancestor of the Waikato people appeared. Kahu (also known as Kahupeka, Kahupekapeka, Kahukeke, or Kahurere) was a Tainui woman who experimented with plants – such as harakeke, koromiko, kawakawa and rangiora – as medicinal remedies. She did so during her great journey: walking inland through the King Country while grieving the death of her husband (who in some accounts is Rakataura; in others Uenga). She gave names to different sites along her journey (such as Te Manga-Wāero-o-Te Aroaro-ō-Kahu – ‘the stream in which Kahu’s dogskin cloak was washed’) – these names tell the story of her journey and preserve the history of the land. At some point during her journey she was ill, which may have been why she sought out plants for their medicinal properties. Unfortunately there are many different versions of Kahupeka’s story, and in them there are few mentions of her medicinal experimentations with indigenous flora. In some versions Rakataura doesn’t die, and he and Kahu traverse the countryside naming places together, as explorers.

In Māori culture, practitioners or experts in any skill or art are known as tohunga. The Tohunga Suppression Act 1907 made tohunga status a punishable offence. The Act was repealed only in 1962, and so much of the knowledge surrounding this customary way of knowing has been suppressed – my search for tohunga wahine (female practitioners) who might count as women of science has not produced significant results. However, it is worth noting that the sources I accessed relied upon the written record. Other sources, such as Māori oral histories, may be much more fruitful.

The next Māori woman in science that I was able to find wasn’t born until the 19th century. Makereti Papakura (Margaret Pattison Thom; she also went by Maggie and was of Te Arawa and Tuhourangi iwi) was born to a Māori mother and an English father in the Bay of Plenty in 1873. She was raised by her mother’s aunt and uncle in Parekarangi, a rural area. She didn’t learn English until she was ten years old, speaking only Māori until her father took over her education. After her schooling, Papakura moved to Whakarewarewa, where she became an accomplished tourist guide. She gave herself the surname Papakura after a nearby geyser when a tourist she was guiding asked if she had a Māori surname. Clearly, the name stuck. In 1891 she married surveyor Francis Joseph Dennan; they had one child together before divorcing in 1900. In 1905 she wrote Guide to the hot lakes district. Papakura travelled to England in 1912, and married Richard Charles Staples-Browne. She had first met Staples-Brown when he was on a tour of New Zealand, and had reconnected with him while she was part of a Māori tour party in England. They divorced in 1924, but Papakura remained in England and in 1926 she enrolled at Oxford University, studying a BSc in anthropology. She died on April 16, 1930, only two weeks before her thesis, The old-time Māori – in which Papakura combined customary knowledge with scholarly conventions – was due to be examined. It was published posthumously, eight years later. Her thesis covers Māori social and familial structures, housing, weaponry and relationship with fire. She was meticulous in her writing, and wrote letters to her people in New Zealand during her drafting process, to ensure her account was as accurate as possible.

Bessie Te Wenerau Grace (1889-1944; Ngāti Tūwharetoa) was the first Māori woman university graduate, graduating from Canterbury University with a BA in 1926. She was the granddaughter of Ngāti Tūwharetoa chief Horonuku Te Heuheu. She then went on to receive an MA with first-class honours in modern languages from London University. In London she also became a nun, Sister Eudora. She worked as headmistress of St Michael’s School in Melbourne. In 1945, Dame Mira Szászy (1921-2001; Ngāti Kurī, Te Rarawa, and Te Aupōuri), a prominent Māori leader, became the first Māori woman to graduate with a degree from the University of Auckland. She went on to complete a postgraduate diploma in social sciences from the University of Hawaii and worked hard to improve the welfare of Māori women throughout her life. In 1949, Rina Winifred Moore (1923-1975; Ngati Kahungunu, Rangitane and Te Whanau-a-Apanui) graduated from the University of Otago with a Bachelor of Medicine and Bachelor of Surgery – and in so doing, became the first Māori woman doctor in New Zealand. In her career she worked to improve public perceptions of the mentally ill and was one of the first doctors in New Zealand to prescribe the contraceptive pill.

It has been harder for Māori and Pacific Islanders to enter scientific professions, as they are forced to combat social prejudices that expect them to fail – that tell them this is not where they belong. It has been harder for women to enter scientific professions because, again, they have to fight against the social biases that tell them ‘this is not your world’. Until the late 20th century, many women were expected to give up their careers when they married – motherhood and the domestic sphere became their full-time responsibilities. Some women chose to remain unmarried and childless in pursuit of scientific careers, while others stopped working when they married. Māori and Pacific women have to fight both gender and racial biases for their place in the world of science. This has been the case throughout the post-contact history of Aotearoa, and continues to be so.

Dr Ocean Mercier. Image courtesy of Dr Mercier and Image Services, Victoria University of Wellington.

Today, there are increasing numbers of Māori and Pacific Island women in science, with some of them working at the intersection of traditional knowledge and western science. Dr Ocean Mercier (Ngāti Porou) is a Senior Lecturer in Māori Science (the intersection of western science and mātauranga Māori) at Victoria University of Wellington. She has a PhD in Physics and was awarded the New Zealand Association of Scientists (NZAS) inaugural Lucy Cranwell Medal (previously the Science Communicators’ Medal) in 2017. Science researcher Hokimate Harwood (Ngāpuhi) combines western scientific and Māori customary knowledge in her research of the feathers in kahu huruhuru (feather cloaks). Her use of microscopy to identify the origins of feathers used in precious cloaks has been pioneering. She is a Bicultural Science Researcher at Te Papa. Her sister, Dr Matire Harwood (Ngāpuhi; PhD MBChB), is a Senior Lecturer at the University of Auckland Medical School and has done crucial research into indigenous healthcare throughout her career. Her efforts have been widely recognised, and in 2017 she was awarded a fellowship to the L’Oréal UNESCO For Women in Science programme.

Dr Hiria McRae. Image courtesy of Dr McRae and Image Services, Victoria University of Wellington.

Victoria University science educator Dr Hiria McRae (Te Arawa, Tūhoe, Ngāti Kahungunu) has created and developed a new educational model aimed at raising Māori students’ engagement in high schools. Through her research projects she has made important contributions to the field of Māori education.

Dr Pauline Harris. Image courtesy of Dr Harris and Image Services, Victoria University of Wellington.

Victoria University astrophysicist, science lecturer and research fellow Dr Pauline Harris (Rongomaiwahine and Ngāti Kahungunu), who has a PhD in astroparticle physics, is a key figure in the revitalisation and teaching of Māori astronomy. She is also involved in the search for extra-solar planets. Connected to Harris’s Māori astronomy programme is Pounamu Tipiwai Chambers, an undergraduate student at Victoria University who has employed Māori astronomical and navigational knowledge in undertaking waka voyages across the Pacific.

Another remarkable young woman, Alexia Hilbertidou (of Greek and Samoan descent), has founded GirlBoss New Zealand, an organisation aimed at the empowerment of young women in STEM studies after she felt alienated as the only girl in her year thirteen physics for engineering class. She was also part of NASA’s SOFIA project, making her the youngest person ever to be part of a NASA mission.

My blog post aims to contribute towards the unmasking of Māori and Pacific women’s contributions to science in both historical and contemporary landscapes. We are already seeing some important changes: many Māori women in science today combine customary and scientific knowledge to great success, a road paved by Makereti Papakura and her BSc thesis. However, Māori and Pacific women are still dramatically under-represented in fields of science, particularly at senior and management levels. It is therefore important that we keep up the momentum of positive change not only by looking forward but also by looking back: the successes of past figures provide an encouraging bevy of ‘shoulders to stand on’ for women in science today.

This post was written as part of my summer scholarship research on the Hidden Networks project, supervised by Rebecca Priestley and Kate Hannah.

Further reading

If you’re interested in learning more about the women I’ve mentioned, you might enjoy some of these sources:

Author

Beth Rust is a BA(Hons) history graduate from Victoria University of Wellington. For her Honours thesis she researched the writings of Christine de Pizan, a 15th-century humanist and early defender of womankind. This past three months she has been working as a research assistant on the project ‘Hidden Networks: hybrid approaches for the history of science’. Beth is just about to start a job in the public service, and she is very excited to take the skills she has learned from her summer research into her new role. She loved being a summer scholar.

How machine learning can perpetuate racism

How machine learning can perpetuate racism

by | Feb 2, 2018 | | 0 Comments

I wrote this algorithm to classify people by gender, but one of the biggest things I learned was how machine learning can reinforce racism and perform poorly on ethnic minorities.

Machine learning – or programs that are able to learn from and improve on past experience and data – is often accused of reinforcing human biases such as racism and sexism. However, it can be a bit unclear how exactly this happens.

How does an automatic soap dispenser fail to recognize black people’s hands? How does image recognition software come to classify people in kitchens as women, regardless of their actual gender? How does artificial intelligence that seeks to predict criminal recidivism produce results that are consistently biased against black people?

This walk-through hopes to give you a bit of an insight into one example of racism in machine learning, and how this comes to be.

The algorithm will be used as part of research into gender equity in STEM fields in New Zealand. A lot of information about who works in certain research centres or who graduated from university is publicly available online (for example, here are university records from NZ between 1870 and 1961), but it doesn’t explicitly include their gender. While a person reading the information can usually guess their gender quite easily and with a high degree of accuracy, it’s obviously very impractical to read and classify thousands or hundreds of thousands of observations. This is where this algorithm hopes to simplify and speed up the process of identifying women in STEM fields.

Training and testing data: Selecting appropriate data

Getting good data for the training and test sets is a really important part of machine learning. Your model is only as good as the data you train and test it on, so getting this right is key.

The starting point of my dataset is the 100 most common names for boys and girls born in New Zealand in each year, going back to 1954. One major drawback of this dataset is that it only includes people born in New Zealand, not those that emigrated here. This means the dataset is almost exclusively made up of Anglo-Saxon names, and does not reflect New Zealand’s large Asian and Pacific populations.

It also doesn’t include any Māori names, presumably because the Māori population isn’t large enough for these names to make the top 100 list. I’ve tried to remedy this by adding the top 20 Māori names for boys and girls from several years to the dataset. However, 91% of the training dataset is still made up of Anglo-Saxon names, while only 9% is made up of Māori names.

These biases in the training dataset mean that the model is likely to recognize the patterns that indicate gender in Anglo-Saxon names, while not picking up on patterns that indicate gender in the names of other cultures. The same biases in the testing dataset mean that the accuracy of the model probably only applies to Anglo-Saxon names, and that it may do much worse on names of other nationalities.  

Selecting useful features for the algorithm

It’s important to consider what features would be most useful in predicting the desired classes. I started off by using the last letter of each name to predict gender. Most Anglo-Saxon names for men end with a consonant, while most Anglo-Saxon names for women end with a vowel.

There are also some pairs of letters that are more common for one gender than the other. For example, the last letter ‘n’ is indicative of a male name (e.g. Brian, Aidan, John), but the suffix ‘yn’ is indicative of a female name (eg. Robyn, Jasmyn). Because of this, using both the last letter of each name and the suffix as features results in higher accuracy than just using the final letter. This gave me an accuracy of about 73% on a testing dataset that includes both Anglo-Saxon and Māori names.

This overall accuracy is lower than it would have been on a testing dataset made up of only Anglo-Saxon names because these features don’t perform as well with names of other origins. In a New Zealand context, this causes the most problems with Māori names. Most Māori names end in vowels, regardless of gender (examples of male Māori names include Tane and Nikau, while female Māori names include Aroha and Kaia). This means this particular feature doesn’t do a very good job with names of Māori origin.

The same problem would likely apply to other ethnicities, too. For example, Japanese, Chinese, Vietnamese, Italian and Hispanic names all often end in vowels, regardless of gender.

Imbalanced classes and the problems they cause

Imbalanced classes, or classes that are very different in their size, can also create problems for machine learning algorithms. In this case, ethnicity is an imbalanced class that is likely to influence people’s names. In the 2013 census, 74% of New Zealanders identified as European, 15% as Māori, 12% as Asian and 7% as Pacific. (Note that Statistics New Zealand allows you to identify with more than one ethnicity, therefore these numbers don’t add up to 100%).

Imbalanced classes often result in high accuracy within the majority class (in this case, European) and low accuracy within the minority classes (Māori, Asian and Pacific). This particular algorithm has an overall accuracy of about 73%. The accuracy within Māori names is about 69%, while the accuracy within European names is 75%.

The class imbalances in the data explain why the overall accuracy may not be a very good way of assessing whether the algorithm is working well. As well as checking the accuracy within each subgroup, it can be a good idea to look at precision and recall for more information on where the algorithm is doing well and where it’s doing poorly.

Precision tells us how much of a classified group actually belongs to that group. In this case, for example, precision of female names is the percentage of names classified as female that are actually female. It is calculated by dividing the number of true positive (number of women classified as female) by all positives (number of women and men classified as female).

Recall is the percentage of a particular group that has been classified as belonging to that group. For example, recall of male names is the percentage of male names that have been classified as male. Recall is calculated by dividing the number of true positives (number of men classified as male) by the number of true positives and false negatives (number of men classified as female).


The tables below show the precision, recall and a couple of other metrics on how well the algorithm is doing. The differences between the overall table and the tables by ethnicity show that it’s likely that this algorithm is systematically worse with non Anglo-Saxon names, specifically Māori names in this instance.

Overall:

precision recall F1 score support
F 0.77 0.76 0.77 274
M 0.71 0.72 0.72 226
avg/total 0.74 0.74 0.4 500

For Māori names only:

precision recall F1 score support
F 0.75 0.88 0.81 17
M 0.33 0.17 0.22 6
avg/total 0.64 0.70 0.66 23

Here we can see that both precision and recall is very low for male Māori names. This means that only a small percentage of the names classified as being male actually are male (low precision) and an even smaller percentage of male Māori names have been classified as being male (low recall).

This is probably because most Māori names end in vowels, regardless of their gender. The algorithm does alright on female Māori names, because it has seen many instances of female names ending in vowels before. But it hasn’t seen many male names ending in vowels, so it fails to classify most of these names correctly.

For European names only:

precision recall F1 score support
F 0.82 0.72 0.77 140
M 0.7 0.81 0.75 115
avg/total 0.77 0.77 0.77 255

Because machine learning algorithms with imbalanced classes usually do worse in the smaller classes, they can further marginalise minority groups by routinely misclassifying them or failing to take into account patterns that are unique to the smaller group. In this example, this is likely to be the case with ethnic minorities.

It seems that this algorithm is likely to really only do a good job on Anglo-Saxon names. This limits the situations in which it would be appropriate to use it, and risks reinforcing Eurocentricity and a focus on whiteness.

This example shows how difficulties in getting hold of representative datasets, selecting features and unbalanced classes can cause algorithms to perform poorly on minority groups. These are only a couple of the many ways machine learning can contribute to the marginalisation of minorities, and it’s important to consider how this might happen in the particular algorithm you’re working on.

The consequences of bias in machine learning can range from the irritation of not being able to get soap out of an automatic dispenser, to the devastation of being given a longer prison sentence. As these algorithms become more and more ubiquitous, it is essential that we consider these consequences in the design and application of machine learning.

See this paper for a more detailed look at how imbalanced classes affect machine learning algorithms.

Author

Emma Vitz is a recent Statistics & Psychology graduate of Victoria University who is starting a new role at an actuarial consulting company in Auckland. Emma enjoys applying data science techniques to all kinds of problems, especially those involving people and the way they think.

Sally Davenport MNZM

Sally Davenport MNZM

by | Jan 19, 2018 | | 0 Comments

What better news to start the year than one of our Principal Investigators featuring on the 2018 New Year Honours List?

Sally Davenport, Professor of Technology and Innovation Management at Victoria University of Wellington, Director of the ‘Science for Technological Innovation’ National Science Challenge and Commissioner at the New Zealand Productivity Commission, has made the list in becoming a Member of the New Zealand Order of Merit (MNZM) for services to science.

Since beginning her career as a science and technology lecturer at Victoria University of Wellington in 1991, Sally has certainly emerged as one the country’s strongest voices and most passionate leaders in the fields of science, technology, management and innovation.

Well done Sally. All of us here at Te Pūnaha Matatini extend our warmest congratulations for your thoroughly well-deserved appointment. Read more about Sally here.

Te Pūnaha Matatini scholar in the news

Te Pūnaha Matatini scholar in the news

by | Dec 14, 2017 | | 0 Comments

Te Pūnaha Matatini Whānau PhD student Caleb Gemmell from the University of Auckland was recently interviewed by the NZ Herald about his ground-breaking research using social network analysis to examine ancient artefact movement in pre-European New Zealand.

Supervised by Principal Investigators Dion O’Neale and Thegn Ladefoged, Caleb’s research stems from work being done in a larger study funded by a Marsden grant.

To read the NZ Herald article and find out more about Caleb’s research, please see here.

Te Pūnaha Matatini researchers receive $4.2M in Marsden funds

Te Pūnaha Matatini researchers receive $4.2M in Marsden funds

by | Nov 9, 2017 | | 0 Comments

Several Te Pūnaha Matatini researchers around New Zealand have been successful in securing major funding for their research, about $4.2 million in total, from the Royal Society Te Apārangi’s 2017 Marsden Fund round.

Marsden Fund applications are very competitive. This year, it distributed an overall total of $84.6 million to more than 130 research projects across the country.

Professor Shaun Hendy, director of Te Pūnaha Matatini, says the current round was the largest number of Marsden projects awarded in one year and one of the highest success rates since 2003. “This is due to the largest real increase in funding since the Marsden Fund was created.”

“It is also pleasing that this large increase in funding didn’t simply lead to more proposals being submitted, which would have lowered the success rate and increased the burden across the sector.”

Successful projects involving Te Pūnaha Matatini investigators

Research supported by the Marsden Fund led by Te Pūnaha Matatini investigators will address diverse range of topics:

  • Professor Stephen Marsland and Associate Professor Isabel Castro (Massey) – AviaNZ: Making sure New Zealand birds are heard ($880,000).
  • Professor Murray Cox (Massey) – From genotypes to phenotypes: Quantifying the functional load ($925,000).
  • Professor Uli Zuelicke and Professor Michele Governale (Victoria) – Supercharging electromagnetism: Tuneable magnetoelectricity in unconventional materials ($905,000).
  • Associate Professor Claire Postlethwaite (Auckland) – Noisy networks: understanding how stochasticity affects mathematical models of cognitive systems ($545,000).
  • Professor Richard Easther (Auckland) – Ultralight dark matter: Dynamics and astrophysics ($910,000).

“It is fantastic to see the success of a number of Te Pūnaha Matatini researchers in the latest Marsden round,” says Professor Hendy. “The Marsden Fund supports fundamental, blue-skies research, so this suite of projects will stimulate and inspire the whole Te Pūnaha Matatini collaboration over the next few years.”

Investigator Professor Marsland says that being awarded the funding means his team can now get down to the business of conducting valuable research. “We can focus research effort on the conservation needs of New Zealand birds, and keep New Zealand at the forefront of methods of adaptive wildlife management, as well as developing novel mathematical methods for dealing with acoustic signals.”

“It also shows us that other people in New Zealand value our approach.”

 

Professor Murray Cox awarded Te Rangi Hīroa Medal

Professor Murray Cox awarded Te Rangi Hīroa Medal

by | Nov 7, 2017 | | 0 Comments

Professor Murray Cox, a computational biologist in the Institute of Fundamental Sciences at Massey University in Palmerston North and a Principal Investigator at Te Pūnaha Matatini, was recently awarded the prestigious Te Rangi Hīroa Medal by the Royal Society Te Apārangi, in recognition of his anthropological work involving the use of genetic data to reconstruct processes of transformation and change in past societies.

Combining genetics and statistical modelling to reveal insights into past societies

Professor Cox’s skills in genetics and statistical modelling have allowed him to ascertain various features of how past societies operated and the social rules they followed, such as those pertaining to marriage (who can marry who).

Using genome-scale data and a novel simulation framework, Professor Cox examined an archetypal example of a key marriage system within a small community on the east Indonesian island of Sumba. His research found that the community had relaxed compliance with the rules, suggesting that marriages were sufficiently flexible to promote social connectivity without negative biological consequences.

Professor Cox has also used statistical modelling to determine how farming expansions across Southeast Asia influenced changes in demographics and social behaviours. Using 2,300 genomic records, individuals with Asian ancestry were found to migrate further and have higher birth rates than individuals with Papuan ancestry.

Early migration from Asia to the Pacific

Another area of Professor Cox’s research is tracing the genetic heritage of the first people in the Pacific. Analysis of ancient DNA from three individuals who were among the earliest to settle in Vanuatu (up to 3,100 years ago) and one of the earliest to settle in Tonga (up to 2,700 years ago), confirmed they were from Asian farming groups rather than of suspected Papuan ancestry.

Pacific people today, including New Zealand Māori, carry Papuan versions of genes. Professor Cox’s research methods have made it possible to investigate how this mixing occurred. They show it was a later mixing, largely driven by Papuan men who came to Oceania and married resident Asian women.

“Genetics has been really powerful at telling us when people moved into the Pacific and what paths they took to get there. But how they acted along the way has largely been a black box,” said Professor Cox.

“It’s only in the last few years that we’ve realised that some of these social behaviours are recorded in the genetics too.  It’s telling a whole new story to interweave with those from archaeology, linguistics and oral history.”

Restoring the mana of Te Wai a Rongo: We cannot value what we do not know

Restoring the mana of Te Wai a Rongo: We cannot value what we do not know

by | Oct 25, 2017 | | 0 Comments

My kaupapa focuses on Māori perceptions associated with the environment, especially freshwater. I wish to impress upon you why the preservation of freshwater is a property rights issue, guaranteed by the Te Tiriti o Waitangi¹, and not an issue of race or ownership. Consequently, I argue that tino rangatiratanga as guaranteed to Māori, and ownership are not the same thing.

It is ironic that New Zealand was sold to English settlers by their peers and settled on the promise of quality soil and clean water. This is because since the signing of the Te Tiriti o Waitangi there has been unprecedented ecological destruction wrought by our mismanagement of water and land in the name of progress.

Protecting our waterways helps to keep Māori culture alive

Māori concerns around land and water policy have always been about affirming tribal proprietary rights guaranteed under the Te Tiriti o Waitangi. Freshwater will always be a taonga and cultural icon to all Māori. The guardianship of freshwater is about keeping alive Māori culture e.g., traditional mātauranga (knowledge), tikanga (protocols) and wairuatanga (Māori spirituality). Many of our sacred tikanga, such as blessings and healing protocols cannot be performed using polluted water. Guardianship of freshwater is more about keeping alive these tikanga, mātauranga and wairuatanga than the concept of ownership in New Zealand law. The draining, altering and pollution of our waterways are opportunities lost to Māori.

The guardianship of freshwater is about maintaining Māori culture and traditions.

Polluted water is an insidious form of colonisation that denies Māori access to their rights, resources and identity. Māori tikanga and kawa, and environmentalist aims around the conservation of water are partly merging; this is mostly in response to the largely negative impact this goal of progress has had on tangata Māori and our natural ecosystems. A fundamental difference between the two groups, however, is the Māori connection via the personification of nature, which is central to Te Ao Māori (the Māori worldview).

Non-Māori often struggle to understand the personification concept, which is part of Māori identity and sense of belonging.  Many non-Maori in New Zealand share this sense of place and connection when a water body is pristine and share a sense of shame, loss, revulsion and disconnect when one is degraded by weeds and pollution. This personification arises from the ontological basis of Māori knowledge- specifically the cosmological foundations for Māori beliefs and action.

The personification of water is a powerful spiritual and emotional connection to nature

Nature- or more accurately Papatūānuku, is our source and end, we are all nurtured by and born upon water, we are all composed mostly of water, and to many Māori we depart on water on our way to the afterlife. To iwi, this personal connection is more a tuakana-teina or senior-junior relationship than a western ownership concept. The water body is the tuakana and we are the junior teina. The tuakana-teina perspectives puts into order those things that can be controlled and those things that are too senior or great to be controlled or ‘owned’. Bottling freshwater, or putting it into other containers will not change this tuakana connection.

To develop a personal connection with water is to take up the challenge of kaitiakianga (guardianship). For instance, when a New Zealander is being reflective while looking at our land and waterscapes, he or she may be musing, “this is beautiful”. However, if one is Māori, one is looking at oneself. We are looking at the sources from which we descend, we are reflecting on our own tīpuna (forebears).

When being reflective and caring about Māoritanga we are also mindful of the values and ideas embodied in wairuatanga, like using water for sacred purposes. If you are looking down into water and contemplating, you see your reflection. In Māori terms, that reflection is your tapu-self, our reflections have moko, because in the traditional Māori worldview, that taonga is you. That is the little thing that makes us feel a bit different from all those worthy government environmentalists, ecologists and conservation biologists striving to protect and nurture our tīpuna. (Sir Tipene O’Regan 1984).

While looking at our land and waterscapes, Māori look inward, reflecting on one’s own tīpuna (forebears).

I am not suggesting that because something is sacred it cannot be used, quite the opposite. Māori have always sought balance, combining old ways of knowing with new ways of doing. What Māori are increasingly saying, is that Te Ao Māori has to be recognised. Māori perceptions must have status in the decision making process if Māori and mātauranga are to be part of the solution.

When the Polynesian explorers first arrived on these shores around 1,000 years ago they were island hoppers and sophisticated resource strippers. It took the best part of another 500 years for Māori culture to evolve the appropriate ecological knowledge and conservation ethic to survive post-megafauna extinctions in Aotearoa. From these lessons we developed important tikanga and wisdom e.g., kaitiakitanga and mātauranga Māori, lessons still relevant today because the stakes are still the same. Extinction.

John K. Perrott

About:

John K. Perrott is Associate Director, Institute of Applied Ecology, Head of Postgraduate Research, School of Science, and Mātauranga Māori Engagement Manager, Research and Innovation Office at the Auckland University of Technology.

Footnote

¹ The term Te Tiriti o Waitangi refers to the Māori version of the Treaty of Waitangi, not the English version. In the Māori text, of Article 2 of te Tiriti, Māori were guaranteed ‘te tino rangatiratanga‘ or the unqualified exercise of their chieftainship over their lands, villages, and all their property and treasures. This would have included water.

Reference

Sir Tipene O’Regan (1984). Māori perceptions of water in the environment. Centre for Māori Studies and Research, University of Waikato, Hamilton, New Zealand. Occasional Paper No. 27.

Acknowledgments

This document was a team effort and I wish to thank the following for their contributions – the late Kaumātua John Marsh, Prof Pare Keiha, Prof Doug Armstrong, Dr Valance Smith, Kaumātua Hare Paniora, Dr Marama Muru-Lanning, Wendy French, Catherine Redmond, and Liana de Jong.

What is WaiNZ?

Kia ora, Aotearoa. We’ve asked leading environmental, social and health researchers to share their personal and professional perspectives about the state of our water and what water means to us as New Zealanders. Follow their blogs right here at tepunhahamatatini.ac.nz and across social media with #WaiNZ.

Where possible, commentary will be backed up by data from Figure.NZ. Their incredible charts are based on data sourced from public repositories, government departments, academics and corporations. Check out their #WaiNZ data board and sign-up to create your very own data board on any topic that interests you.

How we make trust judgments when it comes to scientific information

How we make trust judgments when it comes to scientific information

by | Oct 16, 2017 | | 0 Comments

It is often difficult to find accurate information online, especially when it comes to science-based questions. This is amplified by the fact that scientific findings themselves are revisable or when they are the subject of debate within their respective fields. However, not being able to find concrete answers to scientific questions may lead the public to question and discount the general veracity of science.

Te Pūnaha Matatini invites you to a free lecture by Professor Rainer Bromme, Senior Professor for Educational Psychology, University of Münster, Germany, who will provide an overview of data collected from surveys in multiple countries on the public’s trust in science, and also discuss research on peoples’ capacities to make trust judgments.

In the best case scenario, such judgments are not based on gullible faith in ‘science’, but rather rest on informed trust. Such trust judgments are based on a general understanding of both sides of science as: a system of knowledge and methods for understanding the world and as a social institution for the production and distribution of such knowledge.

Event: The ingredients of informed trust: What citizens (need to) know for coping with science experts

Guest Speaker: Professor Rainer Bromme, Senior Professor for Educational Psychology, University of Münster, Germany

Speaker panel:

  • Professor Shaun Hendy, Department of Physics, University of Auckland (MC)
  • Associate Professor Nicola Gaston, Department of Physics, University of Auckland
  • Dr Daniel Hikuroa, Senior Lecturer, Māori Studies, University of Auckland
  • Dr Cate Macinnes-Ng, Senior Lecturer, School of Biological Sciences, University of Auckland

Location: Auckland Museum

Date & time: Wednesday 25th October from 6-8pm

Tickets are free but bookings are essential.

Please email membership@aucklandmuseum.com or register here to book tickets.

Ngā mihi ki a tātou

Ngā mihi ki a tātou

by | Sep 15, 2017 | | 0 Comments

Kia ora mai tātou,
Ngā mihi ki a tātou.

Tuatahi – tēnei te mihi nui ki ngā kaikōrero, mō rātou whakaaro, moemoea, wawata.
First – our huge thanks to the contributors, for their thoughts, dreams, aspirations.

Tuarua – tēnei te mihi ki a koutou katoa, mo to koutou tautoko.
Second – thanks to all of you who have participated.

Tuatoru – he mihi tino nui ki a FigureNZ mo tō rātou tautoko me pukengatanga o tēnei mahi whakahirahira.
Thirdly – a huge thank you to FigureNZ for their support and expertise on this important work.

We hope the stories that have been shared on WaiNZ have invoked some feelings in you. I certainly have traversed the full range of emotions – anger, disgust, sadness, frustration and despair at the state of water in Aotearoa New Zealand, described in the blogs. But those emotions were tempered with surprise and joy in formative memories shared, and in the collective message of hope for better outcomes for water, and with that hope I trust that we can make better decisions. My anticipation for those better decisions is almost palpable.

I want to expand on some recurring themes that flowed through the blogs. One of those is mauri, the capacity for air, water or soil to support life, the physical life principle, the spark of life. Mauri is a universal concept in Māori thinking and part of a holistic system, expressed beautifully in the idiom – ki uta, ki tai (from the mountains to the sea) – meaning what we do on land impacts the oceans. What is unwritten, but is implicit, is that it is our waterways that provide that connection. If our waterway is muddy – the mauri is compromised; if our waterway is choked with weed – its mauri is comprised; if our waterway is poisoned with pathogens or chemicals – its mauri is compromised; if you drink water and it makes you ill – its mauri is compromised; if our waterway only flows sporadically, or doesn’t flow at all – its mauri is compromised.

We don’t need techno-scientific data to tell us that it is compromised – we can see it, we can feel it. So, although mauri is a Māori word, it is a universal concept and, as many of us have seen and felt, the mauri of the majority of our waterways and increasingly our beaches, estuaries, harbours and oceans has been compromised. The hope I referred to earlier can be activated here – Te Mana o te Wai, for example, is conceptualised in terms of mauri. Mike Joy highlights concerns with the way that water data is represented. However, muddy rivers like those Mary Sewell spoke about don’t lie, rivers choked with weed don’t lie, rivers that are no longer there don’t lie, Siouxsie Wiles informed us about New Zealanders suffering from water-borne diseases that don’t lie, and as Tara McAllister showed us, dogs dying from eating toxins produced by Phormidium don’t lie. So while the empirical data being collected and (mis)represented is of concern, we can realise our own agency by drawing on our own collective experience and observations. Two great examples of where this is happening right now are shared by Ani Murchie and David Hamilton in Waitaha Canterbury and Waiariki, respectively.

The stark reality is that our waterways have been severely degraded and continue to be polluted. The Freshwater Rescue Plan Marnie Prickett discusses provides a beacon of hope, and appears to reflect and align with the hopes and aspirations of many New Zealanders.

I am also concerned with the way we treat water in our urban environments – as a nuisance, something to be controlled, and as a medium to transport our human waste. Civil engineering was once defined as ‘harnessing the powers of nature for human benefit’, however while definitions evolve with human understanding, some practices have not. The continued capture, control and burial of natural water courses is an example of the practice failing to stay abreast of evolving understandings and renewed relationships we seek with our waterways, our ancestors. We need to shift our thinking, as Auckland, for example, persists with live burial of natural water courses in new subdivisions while sporadic stream daylighting projects are show-cased as best-practice. We need to shift thinking away from the idea that ‘we only capture a small percentage of freshwater – the rest is wasted’. The Te Pūnaha Matatini project ‘Mai i ngā maunga ki te tai’ that is about to start is an example of shifted thinking – we draw from mātauranga Māori and complexity science.

We can do this New Zealand, and in fact we must.
Tuturu whakamaua kia tina, haumie, hui e, taiki e.

Siouxsie and Dan

About:

Dr Daniel (Dan) Hikuroa, a Principal Investigator at Te Pūnaha Matatini, is an earth systems scientist at the University of Auckland who integrates mātauranga Māori (Māori knowledge) and science to realise the dreams and aspirations of the communities he works with. Dan’s many projects include the co-writing of the 2014 State of the Hauraki Gulf Environment Report.

Dr Siouxsie Wiles is Deputy Director (Outreach and Public Engagement) of Te Pūnaha Matatini. She describes herself as a microbiologist and bioluminescence enthusiast. As Head of the Bioluminescent Superbugs Lab at the University of Auckland, Siouxsie combines her twin passions to understand the interplay between environment and infectious diseases.

What is WaiNZ?

Kia ora, Aotearoa. We’ve asked leading environmental, social and health researchers to share their personal and professional perspectives about the state of our water and what water means to us as New Zealanders. Follow their blogs right here at tepunhahamatatini.ac.nz and across social media with #WaiNZ.

Where possible, commentary will be backed up by data from Figure.NZ. Their incredible charts are based on data sourced from public repositories, government departments, academics and corporations. Check out their #WaiNZ data board and sign-up to create your very own data board on any topic that interests you.

Restoring the mana of the Rotorua/Te Arawa lakes

Restoring the mana of the Rotorua/Te Arawa lakes

by | Sep 14, 2017 | | 0 Comments

Something interesting has been happening in the Rotorua/Te Arawa lakes over the past decade or so. Instead of separating into factious groups, government, NGOs, iwi, members of the farming community, scientists and the wider community have united in kōrero and actions to support restoration efforts on the lakes. Perhaps this is a model for Aotearoa to follow?

This whakarāmemene has been made possible by a number of interesting developments. Leaders such as Dr Ian Kusabs (Ngāti Tūwharetoa, Te Arawa, Ngāti Maru) have been researching and practicing mātauranga Māori and indigenous fisheries (kaimoana) management in the Rotorua/Te Arawa lakes in recent years. This work not only provides a means for iwi and hapū to exercise mātauranga but it is now being recognised as a scientifically defensible method to compliment conventional water quality indicators and better describe the health and wellbeing (i.e., the mauri) of the lakes. These types of models are desperately required for the goals of Te Mana o Te Wai to be exercised and achieved as part of the National Policy Statement for Freshwater Management (2017).

The community-led Lakes Water Quality Society has had a long history of involvement in protection and restoration of the Rotorua/Te Arawa lakes, through its own leaders, including Ian McLean and John Green. More recently, it has reached out to engage local kaumātua, for example Sir Toby Curtis, Willie Emery, Dr Ken Kennedy, Tai Eru and Geoff Rice. These kaumātua bring new perspectives akin to ‘ki uta ki tai’ and recognising that the restoration of the lakes is just the beginning with efforts that must extend across all rohe, from the top of the catchment to the receiving moana.

Farming groups in the Rotorua/Te Arawa lakes have adopted a highly science-based perspective in their own practices. They are cognisant that the lakes are tohu (indicators) of their own activities, with the mauri of the lakes reflecting the efficiency of their farming activities within the lake catchments. Farming leaders such as Chris Sutton, in the Lake Rerewhakaaitu catchment, have pushed through the initial resistance to change of farmers in this catchment. This farmer group is now starting to drive the regional management authority, Bay of Plenty Regional Council, to do things better; to implement well-informed plans and policies that allow them to simultaneously manage their business and be involved in lake management under a stable regulatory environment.

Regional and local governments have also engaged with the community more than ever before. They have had the benefit of a stable, evidence-based approach from science providers such as the University of Waikato, NIWA and GNS. Their own leaders, such as Andy Bruere from the Bay of Plenty Regional Council, have also recognised the importance of engagement with iwi and the local community, using hui to listen attentively to the needs and aspirations of iwi and hapū, as well as the local community. This is no longer consultation; this is full immersion and collective decision making.

Connecting these pillars for effective lake management will always be challenging, but the features of the Rotorua/Te Arawa Lakes Program need to be examined and propagated more widely. To provide a final perspective, we should examine the goals of the Rotorua/Te Arawa Lakes Strategy Group which was established between Rotorua District Council, Te Arawa Lakes Trust and the Bay of Plenty Regional Council to provide leadership for restoring the lakes:

Me huri whakamuri, Ka titiro whakamua

In order to plan for the future, we must look to the past

David Hamilton

About:

David Hamilton is the current Deputy Director of the Australian Rivers Institute, Griffith University, Brisbane. He served as the inaugural Bay of Plenty Regional Council Chair in Lake Restoration, University of Waikato, for 15 years (2002-2017) following 12 years at the Centre for Water Research, University of Western Australia, and PhD study on shallow lakes at the University of Otago. He has more than 250 publications in the area of lake restoration and biogeochemical processes in aquatic systems, and has provided research supervision to a large number of PhD, Masters and Honours students.

What is WaiNZ?

Kia ora, Aotearoa. We’ve asked leading environmental, social and health researchers to share their personal and professional perspectives about the state of our water and what water means to us as New Zealanders. Follow their blogs right here at tepunhahamatatini.ac.nz and across social media with #WaiNZ.

Where possible, commentary will be backed up by data from Figure.NZ. Their incredible charts are based on data sourced from public repositories, government departments, academics and corporations. Check out their #WaiNZ data board and sign-up to create your very own data board on any topic that interests you.