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Record W2970257718

Reflecting Bicultural Mechanisms in Waterscape Design and Planning in Aotearoa New Zealand

2019· dissertation· en· W2970257718 on OpenAlexfundno aff
Emily Bowerman

Bibliographic record

VenueThe Atrium (University of Guelph) · 2019
Typedissertation
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
FundersUniversity of Guelph
KeywordsAotearoaBiculturalismGeographySociologyGender studiesPsychology
DOInot available

Abstract

fetched live from OpenAlex

Colonial urbanization in Aotearoa New Zealand has caused detriment to waterways that have cultural, economic and environmental significance to Māori. Supported by extensive academic literature, a paradigm shift recognizes opportunities to empower the Māori worldview as an equal guiding voice in practice. A national example being the Whanganui River Agreement (WRA), awarding the River equal rights as humans in federal law. The WRA showcases an unprecedented example of Māori cultural water values upheld within a Western framework. The research seeks to understand the ways practitioners; landscape architects, planners, designers and environmental managers, uphold bicultural water values when designing or managing waterscapes in New Zealand. Waterscapes are defined as a landscape in which water relationships are central to community social, ecological, recreational, spiritual and cultural interactions. This study contributes professional discourse toward waterscape design and planning in Aotearoa New Zealand, and opportunities to employ a bicultural lens to achieve collaborative outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.312
Threshold uncertainty score0.621

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.015
Scholarly communication0.0060.003
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.077
GPT teacher head0.245
Teacher spread0.168 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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