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Exploring Identity and Change in Nonprofit Organisations: An Employee-Level Perspective

2007· article· en· W34192157 on OpenAlexfundno aff
Jennifer Frahm, Cameron Newton

Bibliographic record

VenueBMJ Open Ophthalmology · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsnot available
FundersPublic Health Agency of Canada
KeywordsIdentity (music)Public relationsOpenness to experiencePerspective (graphical)BusinessOrganizational identityOrganizational changeIdentity changeCorporate identityQualitative researchSociologyPolitical scienceSocial psychologyPsychologyOrganizational commitment

Abstract

fetched live from OpenAlex

This paper addresses the crucial issue of how nonprofit employees respond to organisational change. After noting the lack of empirical work on nonprofit organisations and organisational change, we report on part of a larger research project addressing how nonprofit employees cope with identity shift (such as from a community identity to a corporate identity). A survey of 181 nonprofit employees reveals that being open to change is easier for those who possess a corporate identity and more difficult for those who maintain a community identity. The scale of change matters; with incremental change significantly and negatively related to openness to change. The qualitative analysis suggests that nonprofit employees in this sample struggle with identity shift and that group identity acts as a buffer to the potential strain associated with managing the change in nonprofit organisations. Implications for management of nonprofit employees are discussed in light of these findings.

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)0.006
metaresearch head score (Gemma)0.006
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 score0.006
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.008
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0010.002
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 head0.568
GPT teacher head0.516
Teacher spread0.052 · 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
Published2007
Admission routes1
Has abstractyes

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