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Record W3166747656

Evaluating Ocean Perceptions and Ocean Values: The Canadian Ocean Literacy Survey

2021· article· en· W3166747656 on OpenAlexvenueaboutno aff
Lisa Glithero, David B. Zandvliet

Bibliographic record

VenueCanadian journal of environmental education · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsnot available
Fundersnot available
KeywordsLiteracyPerceptionMarine researchSurvey data collectionGeographyPsychologyOceanographyPedagogy
DOInot available

Abstract

fetched live from OpenAlex

This paper describes the development, validation, and key findings of the Canadian Ocean Literacy Survey. Led by the Canadian Ocean Literacy Coalition (COLC) and its research partners, this survey was developed as part of a Canada-wide, mixed methods research initiative examining how ocean literacy is understood and practised across different regions and sectors. The survey included items linked to ocean perceptions, values, and actions as reported by two categories of Canadian respondents: “ocean-engaged” (n=1,359) and “general public” (n=1,010). The survey objectives were as follows: to determine if Canadians would identify Canada as an “ocean nation”; to uncover meaningful patterns in ocean awareness, perceptions, and values by region and subgroups; and to better understand Canadians’ emotional connections to, and relationship with, the ocean, as well as their behavioural intentions and actions.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0040.000

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 head0.017
GPT teacher head0.271
Teacher spread0.254 · 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.

Study designObservational
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

Citations8
Published2021
Admission routes2
Has abstractyes

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