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Record W2730637663

Exploring the Achievement Gap from the Perspective of Parents of African Nova Scotia Learners: Promoting Home and School Connections

2017· article· en· W2730637663 on OpenAlexaboutno aff
Mary Jane Harkins, Barbara Hamilton-Hinch, Diana Seselja

Bibliographic record

Venue2017 Conference of the Canadian Society for the Study of Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsTruancyNova scotiaPerspective (graphical)PedagogyAbsenteeismPsychologyAcademic achievementSociologySocial psychologyCriminology
DOInot available

Abstract

fetched live from OpenAlex

Africian Nova Scotia learners continue to experience inequities within the education system. On the one, students, with the best of interntions and an eagerness towards their success in school, begin to feel disenfranchised, fearful, and find a lack of resources and supports that are reflective of their lived experiences. On the other hand, school administrators often report concern over frequent absenteeism, lateness for class, poor academic performance, truancy, and discipline issues with African Nova Scotian students, particularly male students. These students are at-risk of becoming early leavers, being 'pushed out,'or suspended from high school. While there are studies that explore this achievement gap from the educators' perspective, there is limited research on students' schooling experiences from the perspective of parents. This study, based on Bronfenbrenner's ecological framework, explores the perspective of parents of African Nova Scotian children in public schools in grades six to nine. The overarching question of the focus gropus examines the strengths and barriers to learning from the perspective of parents' own schooling experiences, as well as the present experiences of their children. The findings will be of interest to teachers, teacher educators and policy makers.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.226
GPT teacher head0.380
Teacher spread0.154 · 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 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

Citations1
Published2017
Admission routes1
Has abstractyes

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