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Record W2763593876

Point-in-Time Evaluations of Ontario Municipal Official Plans: Counties

2017· dataset· en· W2763593876 on OpenAlexaboutno aff
Asheika Sood, Leela Viswanathan

Bibliographic record

VenueQSpace (Queen's University Library) · 2017
Typedataset
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousPopulationGeographyTreatyGovernment (linguistics)Plan (archaeology)Library sciencePolitical scienceLawComputer scienceDemographySociologyArchaeologyEcology
DOInot available

Abstract

fetched live from OpenAlex

Being a point-in-time review of the Official Plans, means that while these documents are accurate between May-August 2017, from time-to-time they may undergo changes that will not be tracked by this study. The goal of this review was to get an overall sense of how Indigenous peoples are included in OPs at the time, but this study is unable to account for the evolving nature of these documents. County data tables were used to collect general information about the municipalities. Information was collected on the following attributes: a. Database Name b. Municipality c. Type of Municipality d. Region, County, District, or Single Tier e. County Within f. Official Plan Prior to 2014 g. Amendments before 2014 h. Official Plan Post 2014 i. Amendments after 2014 j. Number of Indigenous Communities k. Names of Indigenous Communities l. Treaty Territory m. Population n. Year Collected o. Website p. Comments q. Sources This information was collected through online source material. Indigenous communities were located by looking at the maps sourced below, as well as by researching Indigenous service providers in these municipalities. Where data was taken from sources outside of the ones listed below, they are listed in the source tab for each row. https://files.ontario.ca/pictures/firstnations_map.jpg http://www.chiefs-of-ontario.org/map https://files.ontario.ca/firstnationsandtreaties_1.pdf Treaty territories were determined by approximating the city’s location on the Ontario Government’s First nations and Treaties Map: https://files.ontario.ca/firstnationsandtreaties_1.pdf Population was determined through Statistics Canada; date of the population data is included in the Year Collected row. The link is included in the source column. Links to Official Plans and amendments found in their respective sections. This was a preliminary data search and some of the files are no longer correct as some of the municipalities sent updated copies.

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)0.015
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.095
Threshold uncertainty score0.374

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.059
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.011
Science and technology studies0.0030.001
Scholarly communication0.0050.002
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.011
GPT teacher head0.234
Teacher spread0.223 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2017
Admission routes1
Has abstractyes

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