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Record W4404787203 · doi:10.1080/00368148.2024.2411761

A Land Exploration-Based Approach

2024· article· en· W4404787203 on OpenAlex
Leonora Rochwerger, Brenda Mason, Leeya Lazarovic, Miga Kim

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueScience and Children · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationScience educationTeaching methodComputer scienceEnvironmental sciencePedagogyPsychology

Abstract

fetched live from OpenAlex

In a Community School located in a First Nation in Northern Ontario, grade 3 students draw on their connection with the land and their own background knowledge through a Land-Exploration-Based Approach to learn about structures and their functions. This method allowed students to become primary investigators in their own learning. In preparation for a summative engineering task, students first engaged in various activities to promote both cultural and scientific understanding. An outdoor Snowshoe Discovery Walk provided the opportunity for students to independently identify various structures found in nature along with the co-creation of working classroom definitions. A comparison of natural and human-built structures found in their surroundings was implemented to further develop foundational learning. In the classroom, students engaged in learning about and constructing beaver dams to cultivate essential engineering and design skills. The culminating activity was introduced through the integration of Indigenous stories to foster cultural relevance in students as they partook in designing and testing an animal shelter of their choosing. This holistic approach to teaching effectively engaged students, promoted curiosity, and built on their knowledge of structures and functions all while developing collaboration and problem-solving skills. Next steps are directed at solution improvement in the design process.

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.

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 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 score0.483
Threshold uncertainty score0.832

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.288
Teacher spread0.271 · 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