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Record W4312399455 · doi:10.24043/isj.400

Views of the islands: The geographical perception of the Balearic Islands among graduate students in primary education

2022· article· en· W4312399455 on OpenAlexvenueno aff
Jaume Binimelis Sebastián, Antoni Ordinas Garau, Maurici Ruiz‐Pérez

Bibliographic record

VenueIsland Studies Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGeography Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionGeographyMental mappingField (mathematics)Balearic islandsFive themes of geographyInformation literacyCartographyPedagogyMathematics educationSociologyPsychologyHuman geographyHistorical geographySocial psychologyEconomic geographyDevelopment geography

Abstract

fetched live from OpenAlex

Geographic literacy is a field of research with a great tradition. This area was first developed in the British and North American academic circles in the 1980s and 1990s, and research has continued until the present day. The analysis of perception and knowledge of geography has focused on the enclaves (toponyms) mentioned in the mental maps (place location knowledge) prepared by university undergraduate students of the primary education teaching major. However, this focus is also on an approach where few studies have been made, yet it has been facilitated by the incorporation of modern geographic information technologies. The authors test a methodology for surface area and perimeter size analysis on the mental maps of the Balearic Islands made by future teachers, comparing their distortions in relation to the real model. After analyzing the results, the most notable common pattern describing the insular students’ perception of the isles is ethnocentrism, which undoubtedly has important implications in the field of geographic education.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.057
GPT teacher head0.377
Teacher spread0.320 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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