Bibliographic record
Abstract
This paper seeks to answer what material quality of life can be expected for someone working in a library in Canada, based on the salaries offered in a data set of three months of job postings on a national job board. The postings were categorized by provincial and municipal location and education level. These data were then compared to census information about the cost of housing in the community where the job was located, to approximate whether the pay was sufficient to provide financial stability, and therefore a good material quality of life. The results of the study show that based on the average of all postings, library workers appear to have a good material quality of life. However, a significant number of individual positions did not provide financial stability. Positions that required an MLIS were more likely to provide a good material quality of life, while positions that required a technician diploma were less likely to do the same. I conducted this analysis with the acknowledgement that library workers exist within communities both in the libraries where we work and in the broader sense of where we live. These contexts have power dynamics, and those who have greater financial stability have a responsibility to advocate for, or stand in solidarity with, other members of the community who have less.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".