title: Population diversity in Aotearoa New Zealand: Insights from the CaDDANZ research programme

authors: Stone, Geoff

abstract: CaDDANZ was a New Zealand Government-funded project studying the impacts of growing population diversity in Aotearoa New Zealand. The project ran from 2014 to 2020 and was extended to March 2021 due to the effects of the global COVID-19 pandemic. Staffed by a multidisciplinary team of researchers, CaDDANZ aimed to identify changing demographics and the impacts of ethnic and demographic diversity on aspects of economic and social change. This report has synthesised a bundle of key insights that could only have surfaced through the reflection on the interplay between the research questions that the original bid set out to address. While we, as a project team, did not intend to produce transdisciplinary or even interdisciplinary work on migration, diversity or the diversity dividend, setting a goal to synthesise something from the project as a whole has produced this report. Using social cohesion as a sorting mechanism for the insights has meant this overview is selective and high level. Not all the projects can be read against a social cohesion or even social inclusion lens. In particular, many of the econometric outputs explicitly addressed aspects of diversity as an economic dividend and that work is not highlighted in the synthesis. 
Three broad themes are addressed 
1. Immigration and diversity – understanding population trends 
2. [Re] conceptualising ethno-demographic diversity in Aotearoa – Tangata whenua perspectives 
3. Diversity in context – in different settings and over time 
The report concludes with four high-level insights 
1. Immigration policy needs to re-examine its position in relation to Tiriti o Waitangi where any Crown partnership relationship is currently lacking. 
2. Despite social cohesion being a negotiated term, its use as a framing for the impacts of migration on both the host country and individual migrant lives is underpinned by its use in the Royal Commission of Inquiry into the terrorist attack on Christchurch mosques on 15 March 2019 and is preferable to the concept of a diversity dividend.1 
3. While ethnocultural diversity is the default for ‘diversity dividend’ research, the concept of the social organisation of difference has broader relevance to social justice-oriented policy development.2 
4. The use of wide range of different methodologies is vital for the production of wellevidenced, theory-informed strategies and policies.

text: Population diversity in Aotearoa New Zealand: Insights from the CaDDANZ research programme CaDDANZ was a New Zealand Government-funded project studying the impacts of growing population diversity in Aotearoa New Zealand. The project ran from 2014 to 2020 and was extended to March 2021 due to the effects of the global COVID-19 pandemic. Staffed by a multidisciplinary team of researchers, CaDDANZ aimed to identify changing demographics and the impacts of ethnic and demographic diversity on aspects of economic and social change. This report has synthesised a bundle of key insights that could only have surfaced through the reflection on the interplay between the research questions that the original bid set out to address. While we, as a project team, did not intend to produce transdisciplinary or even interdisciplinary work on migration, diversity or the diversity dividend, setting a goal to synthesise something from the project as a whole has produced this report. Using social cohesion as a sorting mechanism for the insights has meant this overview is selective and high level. Not all the projects can be read against a social cohesion or even social inclusion lens. In particular, many of the econometric outputs explicitly addressed aspects of diversity as an economic dividend and that work is not highlighted in the synthesis. 
Three broad themes are addressed 
1. Immigration and diversity – understanding population trends 
2. [Re] conceptualising ethno-demographic diversity in Aotearoa – Tangata whenua perspectives 
3. Diversity in context – in different settings and over time 
The report concludes with four high-level insights 
1. Immigration policy needs to re-examine its position in relation to Tiriti o Waitangi where any Crown partnership relationship is currently lacking. 
2. Despite social cohesion being a negotiated term, its use as a framing for the impacts of migration on both the host country and individual migrant lives is underpinned by its use in the Royal Commission of Inquiry into the terrorist attack on Christchurch mosques on 15 March 2019 and is preferable to the concept of a diversity dividend.1 
3. While ethnocultural diversity is the default for ‘diversity dividend’ research, the concept of the social organisation of difference has broader relevance to social justice-oriented policy development.2 
4. The use of wide range of different methodologies is vital for the production of wellevidenced, theory-informed strategies and policies.

year: 2021

title: He tangi mai i te puehu: He whakatewhatewha i te mahi whakamāori me te reo ā-tuhi a ngā tūpuna

authors: Apiata, Hāwea

subjects: Māori spirituality

abstract: Kei te pūtahi o tēnei tuhinga whakapae ko te whakatewhatewha i te whakapapa o te whakaaro Māori (Māori intellectual history) mā ēnei pātai e rua: He aha ā te Māori i tuhituhi ai i te tōmuatanga o te rautau rua tekau? Ā, he pēhea tāna wetewete i ngā huatau whakawairua nō waho i te ao Māori? 

Ina koa, ko tā te tuhinga whakapae nei he whakaaranga, he whakaatu hoki i ētahi huarahi e toru hei rangahau i ngā whakapapa o te whakaaro taketake: ko te ketuketu rua mahara (archival research); ko te tātari ariā (conceptual analysis); me te reo e whakamahia ana kia wetewete i te kaupapa. Mā te mahi ketuketu rua mahara e āhei ai ki te wānanga i ngā whakaputanga a Wiremu Takana, he kaituhi, he kaiwhakamāori nō Ngāti Kahungunu. Ka whakaputaina tāna tuhinga tuatahi i te tau 1915. Ā, e rua anō i whakaputaina e ia i te tau whai muri mai i 1916. Ko ēnei tuhinga āna e whakatewhatewha ana i te whakamāoritanga o te rongopai me te āheinga o ngā pūrākau Māori kia whakamārama i ngā whakaakoranga Moromona. Kāore anō kia āta tātaritia, kia āta rangahaua āna pukapuka e tētahi atu o mua. Ko te huarahi rangahau tuarua ko te tātari i te whakamāoritanga o ētahi ariā whakawairua e kitea ana i roto i ngā karaipiture o te Hāhi o Ihu Karaiti o te Hunga Tapu o ngā Rā o Muri nei. E toru ngā ariā kua tīpakongia hei tirotiro, arā, ko heaven, hell me baptism. Ā, hei whakawhānui atu i te titiro ki tēnei kaupapa, ka huritaongia ngā hua o te tuhinga reo Māori, arā, ka matapakina ngā take kia tuhituhi i te mahi rangahau i roto i te reo Māori.

I te mutunga iho, mā te āta wānanga i ngā whakaputanga reo Māori a te Hāhi o Ihu Karaiti (LDS) e whakawhānuitia ai tō tātou māramatanga ki te hītori o te mahi whakaputa pukapuka i roto i te Hāhi, te mahi punenga a te Māori, te whakareretanga o ngā tuhituhinga reo Māori, me te hītori o te Hāhi o Ihu Karaiti i Aotearoa nei.

text: He tangi mai i te puehu: He whakatewhatewha i te mahi whakamāori me te reo ā-tuhi a ngā tūpuna Kei te pūtahi o tēnei tuhinga whakapae ko te whakatewhatewha i te whakapapa o te whakaaro Māori (Māori intellectual history) mā ēnei pātai e rua: He aha ā te Māori i tuhituhi ai i te tōmuatanga o te rautau rua tekau? Ā, he pēhea tāna wetewete i ngā huatau whakawairua nō waho i te ao Māori? 

Ina koa, ko tā te tuhinga whakapae nei he whakaaranga, he whakaatu hoki i ētahi huarahi e toru hei rangahau i ngā whakapapa o te whakaaro taketake: ko te ketuketu rua mahara (archival research); ko te tātari ariā (conceptual analysis); me te reo e whakamahia ana kia wetewete i te kaupapa. Mā te mahi ketuketu rua mahara e āhei ai ki te wānanga i ngā whakaputanga a Wiremu Takana, he kaituhi, he kaiwhakamāori nō Ngāti Kahungunu. Ka whakaputaina tāna tuhinga tuatahi i te tau 1915. Ā, e rua anō i whakaputaina e ia i te tau whai muri mai i 1916. Ko ēnei tuhinga āna e whakatewhatewha ana i te whakamāoritanga o te rongopai me te āheinga o ngā pūrākau Māori kia whakamārama i ngā whakaakoranga Moromona. Kāore anō kia āta tātaritia, kia āta rangahaua āna pukapuka e tētahi atu o mua. Ko te huarahi rangahau tuarua ko te tātari i te whakamāoritanga o ētahi ariā whakawairua e kitea ana i roto i ngā karaipiture o te Hāhi o Ihu Karaiti o te Hunga Tapu o ngā Rā o Muri nei. E toru ngā ariā kua tīpakongia hei tirotiro, arā, ko heaven, hell me baptism. Ā, hei whakawhānui atu i te titiro ki tēnei kaupapa, ka huritaongia ngā hua o te tuhinga reo Māori, arā, ka matapakina ngā take kia tuhituhi i te mahi rangahau i roto i te reo Māori.

I te mutunga iho, mā te āta wānanga i ngā whakaputanga reo Māori a te Hāhi o Ihu Karaiti (LDS) e whakawhānuitia ai tō tātou māramatanga ki te hītori o te mahi whakaputa pukapuka i roto i te Hāhi, te mahi punenga a te Māori, te whakareretanga o ngā tuhituhinga reo Māori, me te hītori o te Hāhi o Ihu Karaiti i Aotearoa nei.

year: 2021

title: Data Quality in Predictive Toxicology: Identification of Chemical Structures and Calculation of Chemical Descriptors

authors: Helma, Christoph

subjects: computer science

abstract: Every technique for toxicity prediction and for the detection of structure–activity relationships relies on the accurate estimation and representation of chemical and toxicologic properties. In this paper we discuss the potential sources of errors associated with the identification of compounds, the representation of their structures, and the calculation of chemical descriptors. It is based on a case study where machine learning techniques were applied to data from noncongeneric compounds and a complex toxicologic end point (carcinogenicity). We propose methods applicable to the routine quality control of large chemical datasets, but our main intention is to raise awareness about this topic and to open a discussion about quality assurance in predictive toxicology. The accuracy and reproducibility of toxicity data will be reported in another paper.

text: Data Quality in Predictive Toxicology: Identification of Chemical Structures and Calculation of Chemical Descriptors Every technique for toxicity prediction and for the detection of structure–activity relationships relies on the accurate estimation and representation of chemical and toxicologic properties. In this paper we discuss the potential sources of errors associated with the identification of compounds, the representation of their structures, and the calculation of chemical descriptors. It is based on a case study where machine learning techniques were applied to data from noncongeneric compounds and a complex toxicologic end point (carcinogenicity). We propose methods applicable to the routine quality control of large chemical datasets, but our main intention is to raise awareness about this topic and to open a discussion about quality assurance in predictive toxicology. The accuracy and reproducibility of toxicity data will be reported in another paper.

year: 2000