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Record W2141607722 · doi:10.1177/0013161x11423391

Walking in Unfamiliar Territory

2011· article· en· W2141607722 on OpenAlexaff
Brown Onguko, Mohamed Abdalla, Charles F. Webber

Bibliographic record

VenueEducational Administration Quarterly · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsTanzaniaApprenticeshipFace (sociological concept)PedagogyEducational leadershipPoliticsProfessional developmentSouth eastInstructional leadershipMedical educationSociologyPolitical sciencePublic relationsPsychologyMedicineSocial scienceGeographySocioeconomics

Abstract

fetched live from OpenAlex

Purpose: The purpose of this study is to describe the preappointment experiences of early-career headteachers in Tanzania and to discuss implications for postsecondary institutions and ministries of education in East Africa. Research Design: Seven novice headteachers in a suburb of Dar es Salaam, Tanzania, completed questionnaires and participated in face-to-face interviews about their preappointment professional and academic experiences germane to their school leadership roles. Themes within the data from the seven case studies were analyzed and are presented. Findings: There are very limited opportunities for formal preparation programs for headteachers. Preparation experiences typically follow an ad hoc apprenticeship model in which aspiring headteachers learn from their current headteachers. Inadequate preparation is reflected in the limited roles of headteachers in schools. Opportunities for collaborative headteacher preparation are emerging across East African countries but are dependent on support from the private sector and political leaders. Recommendations for further research are presented.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.373

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.002
Scholarly communication0.0020.002
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1120.016

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 head0.052
GPT teacher head0.355
Teacher spread0.303 · 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

Citations34
Published2011
Admission routes1
Has abstractyes

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