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Record W4307466454 · doi:10.1080/13632434.2022.2137125

Women’s role in nation building: socialising Saudi female preservice teachers into leadership roles

2022· article· en· W4307466454 on OpenAlexaffabout
Sue L. T. McGregor, Amani K. Hamdan Alghamdi

Bibliographic record

VenueSchool Leadership and Management · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsEducational leadershipSociologyNation-buildingCurriculumPedagogyContext (archaeology)Public relationsPolitical sciencePolitics

Abstract

fetched live from OpenAlex

ABSTRACTThis paper is about socialising Saudi female preservice teachers (PSTs) while they are attending university into the role of educational leadership. This leadership role should be broadened to include nation building per the tenets of Saudi Arabia’s national development plan, Vision 2030. After discussing nation building and profiling the Saudi educational context (including educational reform initiatives), and after explaining Islamic understandings of educational leadership (values and traditions), an overview of the intentionally planned professional socialisation process is presented. The paper culminates in ideas around what an aligned curriculum might contain so Saudi female PSTs are exposed to educational leadership for nation building while at university. With intentional socialisation into this role, upon graduation, they should be more inclined to assume a role in nation building by (a) influencing the educational sector, players, and policies to benefit the nation and (b) convincing other sectors of the value of women and the education sector in ensuring an ambitious nation. Insights apply to other nations engaged in nation building including Arab nations.KEYWORDS: Nation buildingeducational leadershipprofessional socialisation processteacher education curriculumSaudi female preservice teachers Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsSue L. T. McGregorSue L. T. McGregor (PhD, IPHE, Professor Emerita MSVU, Canada) is an active independent researcher and scholar in home economics education, leadership, and philosophy; consumer education, studies, and policy; transdisciplinarity; and research paradigms and methodologies. She is Docent in Home Economics at the University of Helsinki (lifetime appointment recognising international reputation). She is a transdisciplinary ATLAS Fellow, a Karpatkin International Consumer Fellow, and she received the TOPACE International Award (Berlin) for distinguished international consumer educator and scholar. She has published six books, over 200 peer-refereed papers, 35 book chapters, 15 self-published monographs and has delivered 32 keynotes in 14 countries. Most of her scholarship is available at her professional website: www.consultmcgregor.com. Dr. McGregor recently published the acclaimed Understanding and Evaluating Research (SAGE 2018).Amani K. Hamdan AlghamdiAmani K. Hamdan Alghamdi is Full Professor at Imam Abdulrahman bin Faisal University (IAU) in Dammam, Saudi Arabia. Dr. Alghamdi is the founder and first Vice Dean of the female section at IAU’s Faculty of Education, and she is a Higher Education Academy (HEA) Senior Fellow. Her multifaceted education-focused research interests include Saudi education and curricula, KSA higher education including teacher preparation education, infusing analytical and critical thinking into teaching, critical multicultural education, online education and cultural manifestation, financial literacy education in Saudi Arabia, and narrative research. With over 26 years of national and international teaching experience, she is well known in the field of education in Saudi Arabia and abroad. Dr. Alghamdi is also an award-winning scholar (Arabic and English) and widely published with more than 40 Scopus publications including papers in American, Canadian, Saudi, and Australian high impact factor journals. She has presented papers at nearly 10 different international conference venues and edited several book collections.

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)0.004
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.077
GPT teacher head0.299
Teacher spread0.223 · 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 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

Citations4
Published2022
Admission routes2
Has abstractyes

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