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Record W2016776385 · doi:10.1108/13665620810900292

Rural education: learning to be rural teachers

2008· article· en· W2016776385 on OpenAlexaffabout
Barbara Barter

Bibliographic record

VenueJournal of Workplace Learning · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCurriculumOriginalityPedagogyRural managementSociologyCurriculum developmentRural areaPublic relationsPolitical scienceQualitative researchSocial science

Abstract

fetched live from OpenAlex

Purpose This paper draws on research which began in 2006 with students in a graduate course on rural education. Its purpose was to find out what graduate students saw as current issues of rural education, how that compared to the literature, and what they thought supporting agencies such as government and universities needed to be doing to advance rural education. This paper focuses on presenting the findings and initiating a dialogue that leads to further conceptual understanding of ruralness. Design/methodology/approach The inquiry design and implementation is grounded in theories of constructivism and personal practical knowledge. Findings Some of the more common issues for participants in the study such as, curriculum delivery; bussing; teacher training; insecurity in teacher allocations; and threats of consolidation, are synonymous with the literature. The data also points to the need for research in rural schools and rural communities which is set within a rural‐based theoretical framework. Research limitations/implications The study is conducted within the context of one Canadian province using participants from one specific setting. Therefore, the findings represent a localized instance of both curriculum research and literature review. Practical implications The study may serve to illuminate issues which can be expanded and become more global in its practicality. Originality/value The paper provides an example of curriculum research that is founded on the work and learning experiences of students and their instructor. This knowledge can play a significant role in determining future curriculum design; curriculum implementation; teacher training, recruitment, and retention while enhancing community development in rural areas.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0080.006
Scholarly communication0.0060.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.017
GPT teacher head0.301
Teacher spread0.284 · 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 designQualitative
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

Citations55
Published2008
Admission routes2
Has abstractyes

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