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Record W4244962178 · doi:10.32920/ryerson.14638869.v1

Mission (Im)possible? Determining Organizational Ideology by Examining Mission Statements

2021· preprint· en· W4244962178 on OpenAlexaffabout
Agnes Meinhard, Stephanie Schwartz, Femida Handy

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsToronto Metropolitan UniversityVictoria Park
Fundersnot available
KeywordsIdeologyAction (physics)PessimismPoliticsPublic relationsPolitical actionRevenueVoluntary actionPolitical scienceSociologyBusinessAgency (philosophy)Social scienceAccountingLaw

Abstract

fetched live from OpenAlex

This paper is part of a larger project investigating the relative roles of ideology and gender composition in determining organizational structure and behavior. The project’s genesis arose from a study by Meinhard and Foster (2003) that found that Canadian women’s voluntary organizations (WVOs) differed from gender-neutral and men’s organizations on many different measures. Women’s organizations were less likely to adopt a business orientation or pursue new revenue strategies, but were more likely to collaborate with other organizations and more likely to downsize. They also tended to be more pessimistic in their outlook and engaged in more advocacy and political action. Meinhard and Foster (2003) also found that among women’s organizations, those that were members of the Canadian National Action Committee on the Status of Women (NAC), an umbrella organization for feminist groups, were more extreme in their differences. In other words, although both NAC and non-NAC organizations differed significantly from gender-neutral organizations, NAC organizations differed the most. Keywords: CVSS, Centre for Voluntary Sector Studies, Working Paper Series,TRSM, Ted Rogers School of Management Citation:

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)0.003
metaresearch head score (Gemma)0.010
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.068
GPT teacher head0.387
Teacher spread0.319 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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