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Record W3167649660

Coming to Terms with Ocean Literacy

2021· article· en· W3167649660 on OpenAlexvenueaboutno aff
Sarah MacNeil, Carie Hoover, Julia Ostertag, Lilia Yumagulova, Lisa Glithero

Bibliographic record

VenueCanadian journal of environmental education · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsnot available
Fundersnot available
KeywordsTerminologyLiteracyOcean scienceCurriculumScope (computer science)Environmental educationScientific literacyMultidisciplinary approachSociologyPolitical scienceScience educationPedagogySocial scienceOceanographyComputer science
DOInot available

Abstract

fetched live from OpenAlex

The term “ocean literacy” originated in the early 2000s from American ocean science researchers and educators to strengthen ocean science education in the national curriculum. Worldwide, it has been adapted to reflect a more multidisciplinary approach to understanding humans’ relationships with the ocean. Research from the Understanding Ocean Literacy in Canada national study (2019-2020) (Ammendolia et al., 2020; Glithero, 2020; Hoover, 2020; MacNeil, 2020; Ostertag & Ammendolia, 2020; Yumagulova, 2020) identified ocean literacy as a limiting term, unable to capture the scope of Canadian experiences with the ocean continuum (land, freshwater, coastal areas, sea ice, open ocean), and inadequate in encapsulating different worldviews and across different linguistic communities. We discuss the challenges of contextualizing an international term within Canada and present ideas to move toward more inclusive terminology, examining the challenges still ahead in developing relevant terminology and bridging with international initiatives.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score0.997

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 studies0.0000.000
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 head0.002
GPT teacher head0.184
Teacher spread0.181 · 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

Citations10
Published2021
Admission routes2
Has abstractyes

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