NARRATIVES AT WORK: Women, Men, Unionization, and the Fashioning of Identities
Bibliographic record
Abstract
NARRATIVES AT WORK: Women, Men, Unionization, and Fashioning of Identities Linda K. Cullum St. John's: Institute of Social and Economic Research, 2003; 383 pp. How is it that we construct our identities when we are telling stories about our past? As qualitative researchers, what assumptions do we make about what and how people tell us about their lives? Narratives at Work: Women, Men, Unionization and Fashioning of Identities by Linda Cullum is a carefully detailed exploration of these questions through an investigation into how gender, race and class were (re)produced in Job Brothers fish and blueberry processing factory in St. John's, Newfoundland. This accessible book is an excellent resource for feminist qualitative researchers. The initial goal of Cullum's research was to recover the story of formation of Ladies' Cold Storage Workers Union (LCSWU) in 1948, first all-woman union in Newfoundland. As author began interviewing workers (the narrators) about union, she was struck by wide variety of responses, both between their stories and within individual accounts of work at Job Brothers. The stories that narrators told did not neatly fit into coherent themes. Some women told stories that showed LCSWU to be a significant part of their work experience while other women could not recall anything about union at all. Other women told stories that revealed a shifting, sometimes contradictory, experience of union. As a result, Cullum shifted her focus to documenting and analyzing production of meaning and identity formation. To investigate these emerging issues from interviews, she adopted a feminist poststructuralist theoretical framework where language is not privileged as a transparent tool, reflecting social reality and giving unmediated access to a real, fixed and knowable world (p. 28). The purpose of this research was not to discover truth about work processes at Job Brothers or formation of union. Rather, it was an exploration of how identities and social relations are actively created in and through discourse. Cullum's approach was to make data analysis process transparent to reader. At beginning of book, Cullum remarks that data analysis is seldom clearly explicated in published studies (p. 23). Using setting of fish and blueberry processing plant, Cullum explicitly names, discusses and highlights process of data analysis. She addresses difficulties such as locating people to interview, dealing with people who were unwilling to be interviewed, and interpreting interview data. …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".