Bibliographic record
Abstract
We analyze four calls to action issued by the British Columbia Teachers’ Federation (BCTF) president, Jim Iker. These appeals sought to mobilize members during the 2013-2014 collective bargaining that pitted the BCTF against the British Columbia government and the direct employer, the British Columbia Public School Employers’ Association. We apply a “theory of rhetoric” developed by Chaim Perelman to locate and analyze the topics the BCTF president used to persuade his members to adhere to his arguments about the merit of collective action. We argue that the president constructed his rhetoric by visiting five topics—urgency, fairness, futility, agency, and integrity. The first three promoted a utilitarian logic for collective action. Iker used them to persuade teachers, and other stakeholders, that collective action was necessary for addressing the problem—the futility of the bargaining process to produce a negotiated fair agreement due to the government’s reluctance to bargain in good faith. The last two topics—agency and integrity—comprised a rhetoric of comfort and reassurance offering an affective logic for acting collectively. At least some union members, as well as other stakeholders, might have felt that teachers are expected to care for their charges in the classroom rather than on the picket line, by withdrawing services they monopolize. Iker used the topics of agency and integrity to remind everyone that defending students, young teachers, the teaching profession, and the education system was commendable, and reassured them that collectively they would not be ignored and nor would they fail. In short, we have pointed out five topics that the president visited to mobilize his members to collective action. They highlight a unique rhetoric that aimed to persuade teachers to become agents of protest. Our case study methodology did not allow us to generalize our findings, which more research is, thus, needed to corroborate.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".