Becoming congruent: Experiences of counsellors in the development of their authentic selves
Bibliographic record
Abstract
Understanding how counsellors authentically integrate their personal and professional selves into a congruent identity is still in progress. The current study employed an exploratory research methodology to answer the question, what are the experiences of counsellors in understanding and developing their authentic selves in the therapeutic relationship? Six master’s level participants were recruited and engaged in semi-structured interviews. Using reflexive thematic analysis to analyze the data, four themes were generated, each containing subthemes. The four themes included: dissolving fear, which described the outset of the participants’ journeys as counsellors and the returning point for new challenges; surrendering to self, which involved the recognition and trust of innate abilities and knowing; cultivating capacity, which highlighted the advancement of personal awareness and the ability to hold therapeutic space; and aligning with authenticity, which detailed the subjective accounts of the counsellors as their congruent selves. Findings from the present study contribute to the growing body of research that explores how a congruent use of Self benefits the counsellor, client, and therapeutic relationship. Recommendations for counsellors include incorporating personal and professional practices that help refine their inner attunement ability and to continue expanding their awareness of their authentic selves to determine how they want to engage in the therapeutic relationship.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".