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Record W7135228418 · doi:10.29086/10413/24321

Primary school teachers’ stories of acknowledgement and their personal and professional identities.

2025· dissertation· en· W7135228418 on OpenAlexaboutno aff
Khadija. Vorajee

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAcknowledgementNarrativeObject (grammar)Narrative inquiryQualitative researchDiscourse analysisEveryday lifeSet (abstract data type)Grounded theory

Abstract

fetched live from OpenAlex

This study on Primary School Teachers’ Stories of Acknowledgement and Their Personal and Professional Identities explores the narratives of primary school teachers in relation to their lived experiences of Teacher Acknowledgement and the way in which it shapes their personal and professional selves. This leads to the underpinning research question: What are teachers’ lived experiences of acknowledgement in primary schools? Set against the backdrop of a narrative inquiry approach, the study is framed by Axel Honneth’s (1995) theory of recognition, and is further supported by discourse analysis and semiotics as theories to understand how recognition or the lack thereof is ensconced within everyday school contexts. The South African primary school setting, where various structural and social factors influence the teachers’ experiences of recognition and identity, provides the location within which the study is based. Employing a qualitative approach and an interpretivist paradigm, a purposive sample of four level one teachers from the greater Durban area of Verulam and Ottawa, engaged, via online and in-person interactions in arts-based activities, selecting either letter-writing, collage inquiry or object inquiry, followed by unstructured interviews to uncover their narrative realities about Teacher Acknowledgement. Narrative analysis, followed by analysis of the narratives itself served as the data analysis method employed. The stories revealed that acknowledgement, or its absence, significantly shaped their personal and teacher self, their ideas of belonging and their proficiency in work practices. Recognition by various stakeholders such as teachers, learners, management and within broader community circles manifested as integral to teachers’ sense of self. In contrast, stories of misrecognition gave way to emotional instability, feelings of low self-worth, and an erosion of the teacher’s professional roles. The study reveals that teachers’ identities are not fixed, but fluid-like and constantly evolving and moulded by relational and discursive engagements. It also focuses on emotional investments that mirror the yearning for recognition in sites wherein acknowledgement is largely unreliable or non-existent. In highlighting the teacher’s voice and their storied experiences of acknowledgement, the study paves the way for continuous discussions on the formation of teacher personal and professional identity, teacher well-being and the inferences surrounding recognition in schools. The findings argue towards systemic movements about how recognition is engaged within the school context, implying that authentic acknowledgement is not merely an ethical essentiality but a formal imperative for teacher retention and a call for a complete educational overhaul.

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)0.005
metaresearch head score (Gemma)0.017
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 score0.010
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0100.012
Scholarly communication0.0070.007
Open science0.0010.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.064
GPT teacher head0.387
Teacher spread0.323 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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