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An Inquiry into the Impact of Stress on New School Leaders within a Unique Mentorship Experience

2020· article· en· W3113722320 on OpenAlexvenueno aff
Jodie Rommel, Donna Cooner

Bibliographic record

VenueInternational Journal of Education Policy and Leadership · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsnot available
Fundersnot available
KeywordsMentorshipFocus groupPsychologySocial connectednessBurnoutNarrativeMental healthEmotional intelligencePsychological resilienceMedical educationSocial psychologyMedicineClinical psychologySociology

Abstract

fetched live from OpenAlex

This study aimed to identify the sources of stress new school leaders encounter that may influence their mental health. This study used semi-structured focus groups to elicit thick, rich descriptions of participants’ experiences. The extensive data sets were collected over two years from 16 focus group interviews conducted during Colorado State University School Leadership Institute retreats. Narrative analysis of participants’ responses provided findings on the stress they experienced, including fear of failure or insecurity, pressure to perform, isolation, work-life balance, time constraints, and compassion fatigue. The participants identified that this unique mentorship opportunity allowed for self-reflection, self-care, and reconnecting with their purpose; furthermore, participants shared that the School Leadership Institute offered support and connectedness in a safe, non-evaluative environment. They shared the importance of strong building-level team support, the cathartic nature of the focus group interviews, and the positive progression from year to year in their roles.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.880

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 studies0.0000.000
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 head0.231
GPT teacher head0.465
Teacher spread0.234 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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