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Record W4413615622 · doi:10.37119/ojs2025.v30i2.849

7 of 8: Decreased Planning Time as a Barrier to Reconciliation Education

2025· article· en· W4413615622 on OpenAlexaffvenue
Susan Legge, Adrian M. Downey

Bibliographic record

Venuein education · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPeace and Human Rights Education
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsComputer scienceProcess managementChemistryBusiness

Abstract

fetched live from OpenAlex

This article considers the way neoliberal reductions in teacher planning time work to impede progress in reconciliatory education. Methodologically informed by phenomenology, the study described here was qualitative in nature and featured interviews with six Nova Scotia high school teachers who were teaching the social studies course Mi’kmaw Studies 11. This paper represents one consideration from the larger study. It focusses on the ways participants pointed to the restrictions on planning time in their workload as a direct impediment to actualizing reconciliatory work in education. Drawing together the literatures of time and neoliberalism in education, the authors argue that without time to engage with colleagues, to connect with students, and to just think about the process of course building, teachers—both in Nova Scotia and internationally—are being moved away from Giroux’s (2025) idea of educators as transformatory intellectuals. Teachers need time and space to think and feel their way through the complex histories and contemporary contexts involved in reconciliation, and the data presented in this study suggest that Nova Scotia high school teachers currently have neither. To conclude, the authors call on governments, particularly those that profess a commitment to truth and reconciliation in and through education, to make truth and then reconciliation education more than a discursive shift by abating policies that reduce teacher planning time. Keywords: reconciliation, reconciliation education, teaching time, neoliberalism

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)0.001
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 score0.486
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.372
Teacher spread0.356 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2025
Admission routes2
Has abstractyes

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