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Record W2277498958

The Development of a Survey to Assess the Type of Capacity within Nonprofit Sport Organizations

2011· dissertation· en· W2277498958 on OpenAlexaboutno aff
Christopher N. Morrison

Bibliographic record

VenueBrock University Digital Repository (Brock University) · 2011
Typedissertation
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsnot available
Fundersnot available
KeywordsNonprofit organizationCapacity developmentPolitical sciencePublic relationsGeographyEnvironmental planning
DOInot available

Abstract

fetched live from OpenAlex

The topic of organizational capacity and organizational capacity-building has gained importance among Canadian nonprofit sport organizations. This is illustrated by practitioners calling for increased attention to the capacity-building matters of nonprofit organizations, and two critical Canadian federal government documents outlining strategic direction for the nonprofit sport sector. Consequently, the purpose of this quantitative research study was to develop a valid and reliable survey to categorize nonprofit sport organizations into capacity types identified by Stevens (Stevens, 2006). This quantitative research study offers a preliminary development towards achieving a reliable and valid tool for assessing types of nonprofit sport organizational capacity. This research provides interesting insight into what capacity means by organizing the all-encompassing literature into an easy to understand framework. In addition, it sets the stage for future researchers to build upon this survey development process to achieve a reliable and valid capacity measuring tool.

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)0.018
metaresearch head score (Gemma)0.021
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 score0.020
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.045
GPT teacher head0.248
Teacher spread0.203 · 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
Published2011
Admission routes1
Has abstractyes

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