MétaCan
Menu
Back to cohort
Record W1489545965 · doi:10.18438/b84602

After the Data: Taking Action on ClimateQUAL® Results

2013· article· en· W1489545965 on OpenAlexvenueno aff
Elizabeth Mengel, Judith Smith, Elizabeth Uzelac

Bibliographic record

VenueEvidence Based Library and Information Practice · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsTeamworkSession (web analytics)PsychologyFocus groupPsychological safetyDiversity (politics)Medical educationPublic relationsApplied psychologyPolitical scienceComputer scienceMedicineBusinessMarketing

Abstract

fetched live from OpenAlex

Objective – This paper discusses the actions taken by the staff development and training (SD&T) team at the Sheridan Libraries and Johns Hopkins University Museums in response to results of a ClimateQUAL survey. Methods – The team administered the ClimateQUAL Organizational Climate and Diversity Assessment in March 2009 to the 150 staff members of the museums and libraries, and 80% responded. To get at the root of some of the results, the team conducted 23 focus group sessions over the course of two months. In each 90-minute session, 8 open-ended questions were used to probe the staff’s thoughts on the survey results and elicit concrete suggestions for moving forward. Participants were asked to discuss their personal experiences with six areas of concern: procedural justice, distributive justice, structural facilitation of teamwork, psychological safety, communication, and leadership. One year after the original ClimateQUAL survey, the team administered a one-question follow-up survey. Results – The team analyzed and coded the notes taken during the focus group sessions and developed three discrete written summaries for each session: a brief summary of themes, a list of specific actionable suggestions, and a general description of specific scenarios aired in the sessions. From these analyses, the team developed two types of recommendations: quick tactical actions and long-term strategic recommendations. Strategic recommendations were developed in three main areas: fostering a sense of global ownership of organizational issues, improving organizational communication, and improving leadership and facilitation of teamwork. With these recommendations, the team charged managers to take broad ownership of a plan for individual actions. The results of the one-year follow-up survey were mixed. Staff perceived positive change in communication, but indicated that the areas of procedural and distributive justice, psychological safety, and transparency in decision making continued to require improvement. Conclusion – The work of the SD&T team continues, and it is hoped that ClimateQUAL will serve as the foundation for future assessments of organizational health.

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)0.074
metaresearch head score (Gemma)0.179
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.105
Threshold uncertainty score0.392

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0740.179
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0040.001
Scholarly communication0.0070.006
Open science0.0020.005
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.1050.053

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 head0.237
GPT teacher head0.503
Teacher spread0.266 · 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 designObservational
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

Citations3
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueEvidence Based Library and Information PracticeSame topicQualitative Research Methods and ApplicationsFrench-language works237,207