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Record W7133020735

Then and Now, Knowing and Leading: The Lived Experience of Ethnicity and its Implications for College Leadership

2019· dissertation· W7133020735 on OpenAlexaffabout
Stephanie Marie Dimech

Bibliographic record

VenueTSpace · 2019
Typedissertation
Language
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLived experiencePrivilege (computing)Ethnic groupMeaning (existential)Qualitative researchSet (abstract data type)White (mutation)Grounded theory
DOInot available

Abstract

fetched live from OpenAlex

In my research, I set out to ask if lived experiences related to ethnicity shapes and informed college leaders. From the findings, I have concluded that lived experiences of ethnicity do shape and inform college leaders. This was a heuristic exploration that allowed participants to find, discover, and understand the meaning in their lived experiences. I used a heuristic, qualitative research approach with semistructured interviews to question and learn from 10 participants during two interviews over a 1–3-month period. Participants were Maltese, Italian, Portuguese, or a combination, and were leaders in colleges in Ontario. For the purposes of this study, these college leaders were administrators in the positions of Associate Dean/Chair, Dean/Director, manager, and/or senior administration in Ontario. The experience of growing up ethnic, immigrant, and marginal, was juxtaposed to these participants’ experiences of whiteness, being educated, and privileged. Participant histories of marginality and difference were largely dismissed by others against their current positions of status and power. Implications of historical and current lived experiences of marginality on leadership practice were a central focus. The exploration of how participants negotiated, mediated, and reconciled past marginality with current privilege and how this informed their leadership practice was a core tenet of this work. I pursued this research and offer it not to right the wrongs for participants, but rather to inform leadership practice in ways that encourage white stories of marginality to be told; to disarticulate and rearticulate rules and systems that oppress and confine; and to continue to reimagine that whiteness is not sameness. The insights assembled in these findings may be of interest and informative to other scholars who work towards equity and inclusion.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.212
GPT teacher head0.440
Teacher spread0.228 · 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

Citations0
Published2019
Admission routes2
Has abstractyes

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