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Record W2187266409

Geospatial Architecture for The Cree/Naskapi Land Registry System as An Economic Development Mechanism for Canadian Aboriginal People

2011· article· en· W2187266409 on OpenAlexaboutno aff
Gabriel Arancibia

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsCadastreGeospatial analysisLand tenureLand registrationLand information systemGeographyLand managementEnvironmental resource managementLand useEnvironmental planningGovernment (linguistics)Corporate governanceBusinessLand administrationRemote sensingCartographyEconomicsEngineeringFinanceCivil engineering
DOInot available

Abstract

fetched live from OpenAlex

SUMMARY The aboriginal land registry system across Canada varies depending on diverse land rights regime for each First Nation group, such as their vision of the land, ownership and the environment, communal or ancestral land rights. Independently from land right regime, the land registry becomes an important and essential tool for economical development when a geospatial reference is attach to the land properties. Specifically for the Cree and Naskapi people in Northern Quebec, the adoption of a computerize information system allows them to manage their territory and the environment using the land registry as a first source. In addition, this information is essential to support an e-government and e-governance. This paper describes the results of a study for modernizing the analog Cree/Naskapi Land Registry by integrating it into the Indian Land Registry System (ILRS), which was developed by the Ministry of Indians and Northern Affairs Canada (INAC) for the First Nations. This work explains the Cree/Naskapi land rights regime, the conceptual land tenure differences between private land ownership, the legal cadastral issues, the geospatial infrastructure, the importance of land management in the Web, and the benefits in the economic development and land planning to the native communities in Northern Quebec.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.933
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.200
Teacher spread0.186 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations0
Published2011
Admission routes1
Has abstractyes

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