A tale of two Susans: the construction of gender identity on the British Columbia frontier
Bibliographic record
Abstract
Over the last twenty-five years, women's historians have striven with the problem of how to uncover women's lives in the past. The early concern with merely "retrieving" women's life stories has recently been augmented by a more theoretically- informed approach which takes into consideration issues of experience, voice, and representation, and which challenges the notion of absolute objectivity. This study was designed as a contribution to the latter type of historical research informed by the sociological debates on these issues, and was influenced by feminist materialist approaches that insist on accounting for both the content of experiences and the various discursive positions occupied by subjects. Specifically, it examines the bases of identity construction in the lives of two women teachers (Susan Abercrombie Holmes and Susan Suckley Flood) in nineteenth-century British Columbia, a context in which relatively little work on the history of women has been done. Identity is not perceived as given or static, but rather as constructed, changing, and sometimes contradictory. Even those markers of identity commonly called upon to describe a person- such as gender, race, class, religion, and nationality-are seen as problematic, and their ambiguities are discussed in relation to the life stories of the two women. Subsequently, the effects of these "markers" are further adumbrated through an examination of some of the less obvious ways in which the women's identities were constructed. These are all seen as interrelated, and include the influences of their families of origin on the women's earlier lives, especially regarding their education and marriage decisions, their functions as economic agents, their social relationships, and their self-images or self-representations. To the extent that these were fashioned by their gender identity, many similarities can be seen in their lives, but their experiences also diverged (widely or narrowly) as a result of their differences in other aspects, notably racial identity. These differences had a profound effect on the type and degree of material and ideological constraints placed upon them, and thus on the degree to which they were able to shape the construction of their own identities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.048 | 0.027 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".