title: Incorporating indigenous values in corporate social responsibility reports

authors: Schneider, Annika Barbara Sabine

subjects: corporate social responsibility

abstract: Purpose– The purpose of this paper is to show how a major state-owned enterprise in New Zealand uses its annual report to promote the image of an organisation concerned with the local community including Māori, the indigenous people of New Zealand, Māori values and their relationship with the environment.
Design/methodology/approach – This longitudinal single case study of Mighty River Power Limited spans the period 2000 to 2009. It involves detailed examination of the narrative disclosures contained in the annual reports, including photographs, over the period of the study to determine whether Mighty River Power used the annual report to present a favourable image to the organisation’s stakeholders. Indigenous partnerships between the organisation and Māori trusts were also investigated to determine how these contributed to the corporate identity promoted in the annual reports.
Findings – The analysis found that annual report was used to promote the image of an organisation upholding the Māori value of kaitiakitanga as part of its social responsibility to the local community and environment. Māori partnerships and community environmental group sponsorship were featured extensively in the images and narratives, with specific reference to indigenous values.
Originality/value – This paper builds upon previous literature in the field of corporate social responsibility in annual reports and extends it to the state-owned enterprise sector in New Zealand, focusing specifically on the relationship between the entity and the indigenous community in which it operates.

text: Incorporating indigenous values in corporate social responsibility reports Purpose– The purpose of this paper is to show how a major state-owned enterprise in New Zealand uses its annual report to promote the image of an organisation concerned with the local community including Māori, the indigenous people of New Zealand, Māori values and their relationship with the environment.
Design/methodology/approach – This longitudinal single case study of Mighty River Power Limited spans the period 2000 to 2009. It involves detailed examination of the narrative disclosures contained in the annual reports, including photographs, over the period of the study to determine whether Mighty River Power used the annual report to present a favourable image to the organisation’s stakeholders. Indigenous partnerships between the organisation and Māori trusts were also investigated to determine how these contributed to the corporate identity promoted in the annual reports.
Findings – The analysis found that annual report was used to promote the image of an organisation upholding the Māori value of kaitiakitanga as part of its social responsibility to the local community and environment. Māori partnerships and community environmental group sponsorship were featured extensively in the images and narratives, with specific reference to indigenous values.
Originality/value – This paper builds upon previous literature in the field of corporate social responsibility in annual reports and extends it to the state-owned enterprise sector in New Zealand, focusing specifically on the relationship between the entity and the indigenous community in which it operates.

year: 2012

title: Kōkō Kehe

authors: Maxwell, Te Kahautu

abstract: This composition placed first in the Poi Composition section. Kōkō Kehe; this composition is about a fish species namely the Kehe. This composition talks about the appearance of this fish it has grennstone pounamu like colour and a moko tattoo pattern like that of a Māori male. It can only be caught on certain nights by a scoop net of kōkō. March is when the kehe is in its best condition to eat. The best relish for the kehe when eaten is a kūmara. This composition was performed by Ōpōtiki Mai Tawhiti at the Te Matatini World Championship Kapa Haka 2015.

text: Kōkō Kehe This composition placed first in the Poi Composition section. Kōkō Kehe; this composition is about a fish species namely the Kehe. This composition talks about the appearance of this fish it has grennstone pounamu like colour and a moko tattoo pattern like that of a Māori male. It can only be caught on certain nights by a scoop net of kōkō. March is when the kehe is in its best condition to eat. The best relish for the kehe when eaten is a kūmara. This composition was performed by Ōpōtiki Mai Tawhiti at the Te Matatini World Championship Kapa Haka 2015.

year: 2013-11-11

title: Determining word–emotion associations from tweets by multi-label classification

authors: Bravo-Marquez, Felipe

subjects: computer science

abstract: The automatic detection of emotions in Twitter posts is a challenging task due to the informal nature of the language used in this platform. In this paper, we propose a methodology for expanding the NRC word-emotion association lexicon for the language used in Twitter. We perform this expansion using multi-label classification of words and compare different wordlevel features extracted from unlabelled tweets such as unigrams, Brown clusters, POS tags, and word2vec embeddings. The results show that the expanded lexicon achieves major improvements over the original lexicon when classifying tweets into emotional categories. In contrast to previous work, our methodology does not depend on tweets annotated with emotional hashtags, thus enabling the identification of emotional words from any domainspecific collection using unlabelled tweets.

text: Determining word–emotion associations from tweets by multi-label classification The automatic detection of emotions in Twitter posts is a challenging task due to the informal nature of the language used in this platform. In this paper, we propose a methodology for expanding the NRC word-emotion association lexicon for the language used in Twitter. We perform this expansion using multi-label classification of words and compare different wordlevel features extracted from unlabelled tweets such as unigrams, Brown clusters, POS tags, and word2vec embeddings. The results show that the expanded lexicon achieves major improvements over the original lexicon when classifying tweets into emotional categories. In contrast to previous work, our methodology does not depend on tweets annotated with emotional hashtags, thus enabling the identification of emotional words from any domainspecific collection using unlabelled tweets.

year: 2016