Disservice to Society: A Transnational Analysis of the Canadian Hearing Services
Bibliographic record
Abstract
This paper expresses a growing sentiment the author felt as an employee of Canadian Hearing Services, one that is only implied in the Deaf Citizens petition. Namely, that the current operation of CHS is contributing to a disconnect from the Ontario and Canadian deaf communities, but it also signifies a disconnect from something bigger—what the author calls the global deaf network or what Murray (2007) calls “the transnational Deaf public sphere” (p.4)— and therefore the actions taking place at CHS reverberate beyond provincial and national borders. In applying a transnational analysis, the author explores the connections and linkages between CHS and a deaf network that exists globally, which includes CHS’ past participation in large international deaf events and the role of CHS offices in bringing together people who have unique and important experiences engaging with global deaf spaces and networks, and consider if the changes recently implemented at CHS signify an organizational withdrawal from these global spaces and networks. While this discussion only scratches the surface of possible connections linking CHS to a global deaf network, the author aims to add their voice to those calling on CHS to rebuild bridges that have previously linked the organization with deaf networks at local as well as global levels.
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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 | 0.004 | 0.008 |
| Science and technology studies | 0.036 | 0.015 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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; 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".